25 FEBRUARY 2022, VOL 375, ISSUE 6583 Science

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Finland’s 100,000-year tomb for nuclear waste p. 806

Machine learning tackles antibiotic resistance pp. 818 & 889

Michelson & Science Prize highlights autoantibodies in COVID-19 p. 829

$15 25 FEBRUARY 2022 science.org

GORDON RESEARCH CONFERENCES

Neural development, computational materials science, immunoengineering, and more p. 900

The scientific endeavor aims to provide findings, models, tools, and advances to better understand and address the myriad complex challenges facing society. Meeting this goal requires collective objectivity determined by a wealth of individual and diverse perspectives and experiences—a sample as broad as the diversity of disciplines in the scientific endeavor itself. Highlighting the importance and just integration of our multiplicity, the 2023 AAAS Annual Meeting will feature groundbreaking multi-disciplinary research—research that advances knowledge and responds to the needs of humanity. Drawing from work ranging from astronomy to zoology, the program committee seeks proposals that highlight breakthroughs in science and technology and, in particular, those that incorporate the importance of diversity—in its investigators, subjects of study, and translational implications.

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CONTENTS

2 5 F E B RUA RY 2 0 2 2 • VO LU M E 3 7 5 • I S S U E 6 5 8 3

806

NEWS IN BRIEF

798 News at a glance IN DEPTH

801 United Nations to tackle global plastics pollution Research could gain from negotiations to reduce, reuse, and recycle the common material By E. Stokstad

CREDITS: (PHOTO) TAPANI KARJANLAHTI/TVO; (ILLUSTRATION) HANNAH AGOSTA

802 Biden gets pans and praise for dividing top science positions Francis Collins named as science adviser and Alondra Nelson as head of White House science office By J. Mervis

803 Oldest genomes from Africa offer glimpse of complex past Signs of ice age isolation match archaeological clues By M. Price

804 Glowing tumor marker hampers mouse cancer studies Response to protein complicates immunotherapy research By J. Kaiser

FEATURES

817 Inferring human evolutionary history

806 Final resting place

Unified genetic genealogy improves our understanding of how humans evolved

Finland is set to open the world’s first permanent repository for high-level nuclear waste. How did it succeed when other countries stumbled? By S. El-Showk PODCAST

By J. Rees and A. Andrés RESEARCH ARTICLE p. 836

818 Anticipating antibiotic resistance Machine learning can use clinical history to lower the risk of infection recurrence

INSIGHTS

By J.-B. Lugagne and M. J. Dunlop REPORT p. 889

820 Dimerization decrypts antibiotic activity

BOOKS ET AL.

812 Science at Sundance 2022

Direct dimerization simplifies the synthesis of himastatin and elucidates its mode of action

PERSPECTIVES

By M. Smith

816 Losing sleep with age Hypocretin neuron hyperexcitability underlies disrupted sleep quality associated with age By L. H. Jacobson and D. Hoyer RESEARCH ARTICLE p. 838

812

REPORT p. 894

821 A crooked spinning black hole New observations challenge the current understanding of black hole formation By F. Patat and M. Mapelli REPORT p. 874

822 Flashing light with nanophotonics Manipulation and enhancement of scintillation is achieved in nanophotonic structures By R. Yu and S. Fan RESEARCH ARTICLE p. 837

805 Novel viruses highlight risks of Asia’s wild animal trade

824 C. Thomas Caskey (1938–2022)

Sampling of game in China reveals many viral threats By J. Cohen

A visionary architect of genomic medicine By A. Ballabio and H. Zoghbi

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CONTENTS

POLICY FORUM

825 Streamlining ethics review for international health research Single-site review means protection and efficiency By Mark A. Rothstein et al. LETTERS

827 Plans to protect China’s depleted groundwater By C. Zheng and Z. Guo

827 Transparency crucial to Paris climate scenarios

821 & 874

By L. King et al.

828 Response PRIZE ESSAY

829 Why do people die from COVID-19? Autoantibodies that neutralize type I interferons increase with age By P. Bastard

RESEARCH

839 Protein targeting

889 Antibiotic resistance

Mechanism of signal sequence handover from NAC to SRP on ribosomes during ER-protein targeting A. Jomaa et al.

Minimizing treatment-induced emergence of antibiotic resistance in bacterial infections M. Stracy et al.

845 Structural biology Dynamics and mechanism of a light-driven chloride pump S. Mous et al.

852 Nanomaterials

PERSPECTIVE p. 818

894 Organic chemistry Total synthesis of himastatin K. A. D’Angelo et al.

Highly stretchable van der Waals thin films for adaptable and breathable electronic membranes Z. Yan et al.

PERSPECTIVE p. 820

832 From Science and other journals

REPORTS

797 Editorial

REVIEW

859 Immunology

We are all Gang Chen By G. Chen

Trained ILC3 responses promote intestinal defense N. Serafini et al.

930 Working Life

IN BRIEF

835 Solar cells Rethinking the A cation in halide perovskites J.-W. Lee et al. REVIEW SUMMARY; FOR FULL TEXT: DOI.ORG/10.1126/SCIENCE.ABJ1186

RESEARCH ARTICLES

Structural basis of SARS-CoV-2 Omicron immune evasion and receptor engagement M. McCallum et al.

869 Organic chemistry

A unified genealogy of modern and ancient genomes A. W. Wohns et al.

Deracemization through photochemical E/Z isomerization of enamines M. Huang et al.

PERSPECTIVE p. 817

837 Nanophotonics A framework for scintillation in nanophotonics C. Roques-Carmes et al. RESEARCH ARTICLE SUMMARY; FOR FULL TEXT: DOI.ORG/10.1126/SCIENCE.ABM9293 PERSPECTIVE p. 822

838 Neuroscience Hyperexcitable arousal circuits drive sleep instability during aging S.-B. Li et al. RESEARCH ARTICLE SUMMARY; FOR FULL TEXT: DOI.ORG/10.1126/SCIENCE.ABH3021 PERSPECTIVE p. 816

It’s not (all) about you By J. R. Posselt

864 Coronavirus

836 Human evolution RESEARCH ARTICLE SUMMARY; FOR FULL TEXT: DOI.ORG/10.1126/SCIENCE.ABI8264

DEPARTMENTS

874 Black holes Black hole spin–orbit misalignment in the x-ray binary MAXI J1820+070 J. Poutanen et al. PERSPECTIVE p. 821

877 Cancer immunology Molecular signatures of antitumor neoantigen-reactive T cells from metastatic human cancers F. J. Lowery et al.

884 Optics Topological modes in a laser cavity through exceptional state transfer A. Schumer et al.

ON THE COVER

A reconstruction of multiple optical slices from the developing eye of a fruit fly (Drosophila melanogaster) larva. Each observed photoreceptor neuron expresses one of three protein tags (either alone or in combination), corresponding to different colors. The neurons maintain their spatial proximity while sending projections to the brain. The Gordon Research Conference on Neural Development will be held from 7 to 12 August 2022 in Newport, Rhode Island. See page 900 for the Gordon Research Conferences schedule and preliminary programs. Image: Amanda A. G. Ferreira

Gordon Research Conferences ................ 900 Science Careers ........................................ 928

SCIENCE (ISSN 0036-8075) is published weekly on Friday, except last week in December, by the American Association for the Advancement of Science, 1200 New York Avenue, NW, Washington, DC 20005. Periodicals mail postage (publication No. 484460) paid at Washington, DC, and additional mailing offices. Copyright © 2022 by the American Association for the Advancement of Science. The title SCIENCE is a registered trademark of the AAAS. Domestic individual membership, including subscription (12 months): $165 ($74 allocated to subscription). Domestic institutional subscription (51 issues): $2212; Foreign postage extra: Air assist delivery: $98. First class, airmail, student, and emeritus rates on request. Canadian rates with GST available upon request, GST #125488122. Publications Mail Agreement Number 1069624. Printed in the U.S.A. Change of address: Allow 4 weeks, giving old and new addresses and 8-digit account number. Postmaster: Send change of address to AAAS, P.O. Box 96178, Washington, DC 20090–6178. Single-copy sales: $15 each plus shipping and handling available from backissues.science.org; bulk rate on request. Authorization to reproduce material for internal or personal use under circumstances not falling within the fair use provisions of the Copyright Act can be obtained through the Copyright Clearance Center (CCC), www.copyright.com. The identification code for Science is 0036-8075. Science is indexed in the Reader’s Guide to Periodical Literature and in several specialized indexes.

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science.org SCIENCE

GRAPHIC: KELLIE HOLOSKI/SCIENCE

By Y. Ou et al.

E D I TOR IAL

We are all Gang Chen

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ampant wrongful prosecutions terrorize innocent people—everywhere. The scientific community is not immune to this. I know because I was a victim. I am a professor at the Massachusetts Institute of Technology (MIT) who was accused by the US government of fraud and questionable connections to Chinese entities. Earlier this year, I was finally exonerated—it took 2 years. I am painfully aware, however, that I am the luckiest among the unlucky. Many other Chinese American scientists are being unfairly investigated for similar alleged “crimes.” Or they are simply leaving the country to avoid being targeted. My ordeal taught me that politics affects science and scientists, and that universities and funding agencies must stand up for faculty who are wrongfully prosecuted. I grew up in China and found my American dream at MIT, where I became a department head and led a vibrant research group. In January 2020, the dream turned into a nightmare. I was detained and interrogated at Boston’s Logan Airport, and my electronic devices were confiscated. A year later, federal agents raided my home, arrested me, and interrogated my wife without an attorney present. My family lived in fear for 2 years, and members of my research group relocated. The accusations against me were absurd. They criminalized routine professional activities: reviewing research proposals, writing recommendations, and hosting visiting scientists. In January 2022, the US Department of Justice (DOJ) dropped all charges. I was investigated under the DOJ’s China Initiative, an effort launched in 2018 by the Trump administration to counter Chinese government’s espionage and threats to national security. Andrew Lelling, a chief architect of the Initiative and the US Attorney for Massachusetts at the time, rushed my indictment through. Although he recently said, “The Initiative has drifted, and in some significant ways, lost its focus,” similar prosecutions are still going on. Christopher Wray, director of the Federal Bureau of Investigation, said just weeks ago that the agency opens two new China Initiative investigations every day. What gave me hope and ultimately saved me is a lesson for all universities. MIT leadership, under President L. Rafael Reif, supported me morally and

financially after I was detained at the airport, and the university made its support public soon after I was arrested. MIT professor Yoel Fink organized faculty support, which led to an open letter, signed by over 200 MIT faculty. The letter used facts to tear apart the criminal complaint and ended with a rallying statement: “We are all Gang Chen.” A similar online petition launched by Northwestern University professor G. Jeffrey Snyder was signed by 1380 individuals. In open letters, faculty from about 230 universities in the country called on the DOJ to stop the China Initiative. The fundraising that my daughter launched reached its goal in 1 day and helped raise awareness of other Chinese American scientists in a similar plight. New civil rights organizations joined forces with existing ones to fight for justice and eliminate the China Initiative. These collective voices helped compel the government to drop all charges. MIT has supported other faculty under similar investigation, but other universities have mostly remained silent. I urge university leaders, trustees, and alumni associations to protect their faculty from a campaign that is misdirected. The talent loss and terror lobbed upon faculty are weakening their institutions, supporting harmful bias, and ruining lives. Funding agencies must also stand up for justice. Dr. Chris Fall, the former director of the Office of Science at the US Department of Energy (DOE), explained recently that in 2020, the DOE changed reporting rules regarding foreign ties. The government applied the 2020 rules to my 2017 DOE grant application. The 2021 indictment mentioned DOE 18 times, only to miss this basic fact. The DOE should have spoken up when it counted. That is a lesson for all federal agencies. I’ve devoted my life to science and education and never thought that I would get involved in activism. But I am now. People need to raise their voices so that the government and public understand the evil of wrongful prosecutions. I call on Congress to investigate the wrongdoings of the government in my case and similar cases. And I call for continued vigilance to end the China Initiative, however it is repositioned by the DOJ. As Martin Luther King Jr. wrote from a Birmingham jail, “Injustice anywhere is a threat to justice everywhere.” –Gang Chen

Gang Chen is the Carl Richard Soderberg Professor of Power Engineering at the Massachusetts Institute of Technology, Cambridge, MA, USA. gchen2@ mit.edu

PHOTO: MIT

“…wrongful prosecutions terrorize innocent people— everywhere.”

10.1126/science.abo6697

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NEWS IN BRIEF

[Hong Kong’s] hospitals are sandcastles in a tsunami.

“

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University of Hong Kong virologist Siddharth Sridhar, in a tweet describing the impact of the recent COVID-19 surge on the city’s health care system.

2016 in Nigeria’s Borno state. The continent is still battling big outbreaks of vaccinederived polio, however, which occur in areas of low immunization when the live but attenuated virus in the oral polio vaccine regains its ability to paralyze and spread. The Global Polio Eradication Initiative is hopeful that it can stop the spread of the virus in Malawi quickly through a vaccination campaign, as it has done for several other “imported” wild polio outbreaks.

Edited by Kelly Servick

Winter study probes Great Lakes | Researchers from the United States and Canada last week used sleds, snowmobiles, airboats, and icebreakers to fan out across the Great Lakes in a bid to better understand how the five water bodies function in the dead of winter and how climate change is reshuffling their ecosystems. Scientists from 19 research institutions and government agencies participated in the Winter Grab, a weeklong push to collect data at some 30 sampling sites. Fewer than 5% of Great Lakes studies have been done in winter, in part because lakes were long considered relatively dormant when covered by ice—not to mention dangerous to access. As a result, scientists know relatively little about how lake organisms behave during winter or how nutrient cycles vary by season. As warmer winters shrink ice cover, Winter Grab researchers hope their findings will help spur more efforts to study lakes around the world during the coldest months. E C O L O GY

COVID-19

Africa builds mRNA vaccine capacity

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he drive to help African countries produce vaccines with messenger RNA (mRNA) technology got big boosts last week from the World Health Organization (WHO) and the company BioNTech. The success of mRNA COVID-19 vaccines made by the Pfizer-BioNTech collaboration and Moderna led to intense global demand, but African countries have had little access because of limited supply and high prices. Campaigns by several governments and nongovernmental organizations failed to convince the companies to freely share their technologies with economically strapped countries. So last year WHO launched a hub in South Africa to produce mRNA vaccines independently. The agency, which hopes the hub licenses a product by 2024, last week announced plans to train scientists from South Africa, Egypt, Kenya, Nigeria, Senegal, and Tunisia. BioNTech, which has been criticized for trying to undermine the WHO effort, separately announced that later this year it will train local scientists and send modular, shipping container–size vaccine factories to Ghana, Rwanda, and Senegal.

Wild poliovirus back in Africa | In a setback for the global polio eradication campaign, a wild poliovirus has leapt from Pakistan to the African continent, where it has paralyzed a 3-year-old girl in Malawi. The case, announced on 17 February by the I N F E CT I O U S D I S E A S E

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Malawi government, is the first wild polio case in the country since 1992. Pakistan and Afghanistan are the last two countries that are endemic for the wild virus, which means circulation there has never stopped. Occasionally, however, the virus spills over from these entrenched reservoirs. Africa’s last known case of wild polio occurred in

Dinosaurs’ death came in spring | The beginning of the end for dinosaurs was likely one day in spring, according to a study of fish fossils excavated in North Dakota. To pinpoint the season of the Cretaceous-Paleogene mass extinction 66 million years ago, paleontologists analyzed the bones of filter-feeding fish from a site called Tanis. There, the asteroid impact that doomed dinosaurs kicked up a large river wave, burying countless late-Cretaceous era animals and plants. The fish had debris from the impact lodged in their gills, evidence that they had perished within minutes. The researchers used carbon isotopes in the bones to identify seasonal growth layers. (The fish grew faster in spring, when food PA L E O N T O L O GY

science.org SCIENCE

PHOTO: FABIAN BIMMER/REUTERS

The presidents of Ghana, Rwanda, and Senegal visited a modular vaccine lab in Germany.

An elliptical secondary crater on Sheep Mountain in Wyoming.

GEOLOGY

First secondary craters found on Earth point to giant asteroid impact

S PHOTOS: (TOP TO BOTTOM) KENT SUNDELL/CASPER COLLEGE; YASEMIN OZKAN-AYDIN/UNIVERSITY OF NOTRE DAME

cientists have identified a series of 31 craters in Wyoming with diameters from 10 to 70 meters, created 280 million years ago by boulders ejected from a previously unknown cosmic impact. Such “secondary” craters are common on airless moons and planets, but previously have never been identified on Earth. Many scientists suspected the planet’s

was plentiful.) They report on 23 February in Nature that the fish—along with threequarters of life on Earth—perished during spring in the Northern Hemisphere.

Centipedes inspire robot | Centipedes’ ability to speed over rock, sand, and soil has led to a new robot that could prove handy to farmers. B I O L O GY

thick atmosphere would prevent their formation altogether by cracking up boulders on descent. The finding, published this month in the Geological Society of America Bulletin, also suggests a 60-kilometer-wide impact crater is likely buried some 2 kilometers below Wyoming’s eastern border—potentially one of the largest known impacts in North American history.

On land, centipedes move their legs in a wave that switches direction when they encounter obstacles, researchers reported this month at the virtual meeting of the Society of Integrative and Comparative Biology. In water, they wiggle their bodies to move forward. To better understand how the animals coordinate their legs and body in different environments, the researchers built a 70-centimeter robot model and

A robot mimics the leg and body movements of centipedes to move efficiently over uneven terrain. SCIENCE science.org

determined the most efficient timing of leg and body movements. The robot was so adept at moving across a natural landscape that the team has formed a company to develop the device for finding and destroying weeds in agricultural fields.

Psilocybin shows lasting effects | The antidepressant effects of psilocybin-assisted therapy may last at least 1 year for some people, a small follow-up study suggests. In a clinical trial of 24 people with major depressive disorder, researchers found that two doses of the substance found in magic mushrooms, given approximately 2 weeks apart alongside psychotherapy, led to clinically significant reductions in depression severity in 18 participants and remission in 14 of them after 1 year. The results, reported last week in the Journal of Psychopharmacology and discussed in a panel at the annual meeting of AAAS, M E N TA L H E A LT H

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THREE QS

European Commission pushes for gender equality Effective this year, higher education and research organizations must have a gender equality plan to qualify for European Commission research grants. Among other commitments, grantees will be required to train staff about unconscious bias and collect data on staff and students for accountability. Anne Pépin, a physicist at the French national research agency, CNRS, and senior policy officer at the Commission, spoke with Science about the changes and structural barriers for female scientists. (A longer version of this interview is at https://scim.ag/GenderEqEurope.)

Q: What motivated you to get involved? A: When I became a researcher, I was clearly a minority in physics. I didn’t suffer from explicit discrimination. But it was more a cumulative effect—like sometimes people taking you for the postdoc when you’re the permanent researcher. I’ve been involved in pioneering a gender equality plan at CNRS, and I think it can have long-lasting and multiplier effects. We were able to implement a range of actions—for example, sensitizing the recruitment and promotion committees to gender issues and allowing women to have 6 months off teaching duties to concentrate on their research after a maternity leave.

which publishes Science, offer the longest follow-up yet for a randomized study of psilocybin’s antidepressant effect. They extend findings from the same trial, published in November 2020, that revealed improvements for 17 of the 24 participants after 1 month. Other factors may have contributed to the persistent benefit, the researchers note: One-third of participants began treatment with an antidepressant sometime over the course of follow-up study, and nearly half received some form of psychotherapy outside of the study.

Health equity fight loses pioneer | Paul Farmer, an infectious disease physician, anthropologist, and champion of global public health, died suddenly this week at age 62. At the time of his death, he was visiting the University of Global Health Equity in Butaro, Rwanda, that he helped found. Farmer, who was also a professor at Harvard Medical School, dedicated his career to bringing health care to poor and marginalized communities, in particular in Haiti and Rwanda. In 1987, he founded the nonprofit Partners in Health, focused on providing high-quality health care in resource-poor settings and advocating for G L O B A L H E A LT H

human rights and social justice. Farmer’s work also helped inspire global efforts to expand access to lifesaving treatments for HIV and other diseases.

Antarctic pollution melting snow | Burning of fossil fuels in Antarctica is hastening snow melt there, researchers have found. When soot, a byproduct of combustion, settles out of the air, the dark particles absorb sunlight and heat the snow. To estimate the impact, researchers measured soot in snow taken from 28 places across the northern Antarctic Peninsula, including sites near research bases and stops for ships that carry an average of 53,000 tourists per year to the continent. Melting from the ship soot amounts to hundreds of tons of snow loss per person, the group reports this week in Nature Communications. Per person losses are estimated to be an order of magnitude higher near research stations, because of generators, helicopters, and vehicles. In the most polluted areas, the snowpack has declined by 2.3 centimeters each summer. The researchers recommend limits on research infrastructure and surging tourism, as well as improvements in energy efficiency and renewable power. ENVIRONMENT

Q: Why make this a mandatory requirement? A: To some extent, the voluntary

Q: Are you optimistic for change? A: There is still a lot of work ahead, and it’s not all on the side of the European Commission. It also has to be a collective effort with everyone—women, men, genderdiverse individuals—getting onboard to further improve working conditions for all. SCIENCE.ORG/NEWS Read more news from Science online. 800

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SCIENCE AND ART

Yeasty dance video rises to top of Ph.D. contest

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ithuanian scientist Povilas Šimonis’s colorful and catchy interpretation of the electrical stimulation of yeast cells is the winner of this year’s “Dance Your Ph.D.” contest. The annual competition, which is hosted by Science and sponsored by the artificial intelligence company Primer, invites researchers to interpret their theses through movement and to commit the act to video for cash prizes and nerd fame. Šimonis’s doctoral work at Lithuania’s Center for Physical Sciences and Technology and Vilnius University explores how the single-celled fungus that powers bread baking behaves when pulsed with electricity. The performance, which included original music and several sets, casts people as yeast cells prancing amid mouthwatering baked goods. The result beat out 29 other submissions to win both the overall award and the biology category. A judging panel of dancers, scientists, and artists also selected winners in chemistry, physics, and social sciences. See videos from all the winners at https://scim.ag/DancePhD.

science.org SCIENCE

PHOTO: POVILAS ŠIMONIS

implementation of gender equality plans over the last decade by European organizations was a success—we’ve accumulated a wealth of good practices and established practical tools. Still, changes are fragmented and very slow. We’re roughly at gender parity among doctoral graduates, but women only represent 26% of full professors. The institutions will be responsible for identifying the most pressing areas to address based on their data.

IN DEP TH Plastic waste piles up on a beach off Panama City. Nations will try to negotiate a new treaty aimed at reducing the global problem.

ENVIRONMENTAL POLICY

United Nations to tackle global plastics pollution Research could gain from negotiations to reduce, reuse, and recycle the common material By Erik Stokstad

PHOTO: LUIS ACOSTA/AFP/GETTY IMAGES

E

ach year, an estimated 11 million tons of plastic waste enter the ocean, equivalent to a cargo ship’s worth every day. The rising tide—in the oceans and beyond—is just a symptom of much wider problems: unsustainable product design, short-sighted consumption, and insufficient waste management, scientists say. To curb the flood, says Jenna Jambeck, an environmental engineer at the University of Georgia, “we need to take more action and it needs to be further upstream” in the production process. That’s exactly what negotiators from 193 countries are setting out to do when they meet in Nairobi, Kenya, next week. Their ambitious goal: to create a negotiating committee that will try to hammer out, within 2 years, a new global treaty intended to curb plastic pollution. An already released proposal, modeled on the United Nations’s climate treaty, would have nations adopt action plans, set binding waste reduction targets, and establish monitoring systems and a new SCIENCE science.org

global scientific advisory body. “It’s about time,” says Chelsea Rochman, an ecologist at the University of Toronto who has called on nations to tackle the issue. Existing international efforts to reduce marine litter and exposure to hazardous chemicals include some measures related to plastic pollution. But no global treaty tries to reduce pollution by targeting a product’s entire life cycle, from its birth as a raw material to its death—if it becomes trash. Taking such a broad approach to plastics, says Anja Brandon, a policy analyst at the Ocean Conservancy, “is going to be a much bigger scientific endeavor.” For one thing, rigorous, comparable numbers on the scope and sources of the problem are scarce, making it difficult to identify pollution hot spots or detect trends. Nonprofit groups and government agencies use dozens of varying protocols for surveying beach litter, for example. Methods of counting microplastics in water—shed from synthetic fabrics, for example, or formed when large plastic objects degrade—also vary. “There are several holes in the data,” Jambeck says.

The new treaty could help by promoting or establishing standard measuring and accounting methods. One such approach, called environmental economic accounting, is already being used in some countries to track various raw materials. And a method known as mass balance analysis, which tracks the amount of material entering and leaving production processes, holds promise for quantifying the amount of recycled plastic used in new products. Even after scientists settle on standard metrics, collecting those numbers could be a challenge, Jambeck notes, especially in developing nations with relatively weak regulatory and research infrastructures. The United Nations Environment Programme (UNEP), which is hosting the upcoming meeting, has worked to increase monitoring capacity with training programs and online courses. Such efforts would be aided by a new treaty that encourages funding and technological advances. Remote sensing via satellites and drones, for example, could more easily identify plastic pollution trends, reducing the need for labor-intensive ground surveys. 25 FEBRUARY 2022 • VOL 375 ISSUE 6583

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U.S. GOVERNMENT

Biden gets pans and praise for dividing top science positions Francis Collins named as science adviser and Alondra Nelson as head of White House science office By Jeffrey Mervis

ing OSTP in the late 1990s. Lane calls it “an unprecedented experiment” that resident Joe Biden’s decision to could weaken the office’s ability to serve name two people to temporarily fill the president. the top science advice post in his But John Holdren, a physicist who served administration—a job historically in both roles under former President held by one appointee—is drawing Barack Obama, doesn’t see the division of mixed reactions from the U.S. research labor as a problem. “I think both Alondra community, including opposing takes from and Francis are very collegial people and two former presidential science advisers. will work very well together,” Holdren says. Biden said last week he “If the president wants is “doubling down on sciadvice in domains where ence” by appointing genetiFrancis is not an expert, I cist Francis Collins, former have no doubt that he will director of the National talk to Alondra. I don’t see Institutes of Health (NIH), any glitches.” to serve as the president’s Collins, who led NIH for science adviser and social 12 years before stepping scientist Alondra Nelson, down in December 2021, deputy director of the will provide advice on “all White House Office of Scithings science,” says an ence and Technology Policy, OSTP spokesperson, and to serve as OSTP director. will co-chair the PresiBoth jobs were held by gedent’s Council of Advisors neticist Eric Lander, who on Science and Technolannounced on 7 February ogy. Collins will also work he was resigning after a on two of Biden’s research White House investigation priorities: establishing a found “credible evidence” new biomedical research that Lander had bullied agency, the Advanced Reand disrespected staffers. search Projects Agency Biden gave no timefor Health (ARPA-H), and line for nominating a reinvigorating the Cancer permanent replacement Moonshot, which Biden for Lander, who took ofled as Obama’s vice presifice in May 2021. (Neither dent. Collins will not reCollins nor Nelson is in the port to Nelson, the OSTP running, sources say.) In spokesperson says. the meantime, Biden said Nelson would be the this temporary arrangefirst Black woman and ment would “allow OSTP first social scientist to and [my] science and techAlondra Nelson (top) and Francis lead OSTP. Trained as a nology agenda to move Collins (bottom) will share jobs sociologist, she was presiseamlessly forward under previously held by Eric Lander, who dent of the Social Science proven leadership.” stepped down last week. Research Council before Others, however, aren’t coming to OSTP 1 year ago sure the new arrangement is a good idea. as deputy director for science and society, “I don’t understand it, and it doesn’t where she managed programs to improve make any sense to me,” says Neal Lane, an scientific integrity, broaden participation emeritus physics professor at Rice Univerin science and engineering, and ensure eqsity who served as former President Bill uitable access to new technologies. Clinton’s science adviser while leadNelson’s promotion allows her to con-

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PHOTOS: (TOP TO BOTTOM) REUTERS/KEVIN LAMARQUE; NATIONAL INSTITUTES OF HEALTH

More detailed industrial data on plastics production, transport, and consumption could also help nations curb pollution, researchers say. But many countries allow companies to keep such numbers private, making it difficult to calculate how plastic is moving through the economy and into the environment. And no one systematically tracks that information. The Ocean Conservancy, for example, has struggled to find out how much recycled plastic firms are using, Brandon says. Researchers are still pondering which numbers would be most useful, and how the treaty might help make that information more available. Negotiators will also confront a key question: How much plastic pollution is too much? It’s clear that plastic bags, discarded fishing gear, and microplastics can kill wildlife, but scientists are just beginning to figure out how to calculate the risks. The treaty could help catalyze such efforts, says Rochman, who recently helped California regulators devise protocols for setting microplastic thresholds to protect people and ecosystems. The political will to reduce plastic waste will be much higher if it’s known to harm humans, says Karen Raubenheimer, a policy researcher at the University of Wollongong. But she thinks any final agreement is unlikely to call for hard caps on new plastic. “It will be challenging in the short-term to stop using virgin plastic,” Raubenheimer says. A big reason is that many uses of plastic are seen as essential. Single-use plastic items are common in health care, for example, to prevent contamination and infections, and in the food industry to keep fruit, vegetables, and other products from spoiling. Even disposable bottles can be vital in areas without clean water. Negotiators might call for the reduction or elimination of what UNEP has called “unnecessary, avoidable and problematic plastic,” such as single-use shopping bags, takeout cutlery, or plastic beads in cosmetics. But analysts say nations must also focus on ways to reuse and recycle plastic materials. Currently, researchers estimate that less than 10% of plastic products are recycled. Smarter product designs that drive better waste management practices could boost that number, reducing the demand for virgin materials. Trying to finalize the new treaty in just 2 years is “highly ambitious,” UNEP admits. But researchers who have watched the plastic pile up are delighted that the talks are even getting started. “People are putting high level resources to try to solve this problem in a way that we didn’t see a decade ago,” says Kara Lavender Law, a physical oceanographer at the Sea Education Association. “It’s actually astonishing.” j

PHOTO: JACOB DAVIS

tinue to use her expertise in those areas and also apply her skills as a manager, says one of her former mentors, Evelynn Hammonds, professor of African American studies and head of the history of science department at Harvard University. “I think it’s a very good move by the president,” Hammonds adds. “And I think that she and Francis could turn out to be a great team.” The 140-person OSTP staff provide technical expertise to the White House, coordinate research-related policies across the government, and produce a stream of congressionally mandated reports. Its health and life sciences division, for example, is helping coordinate governmentwide efforts on both ARPA-H and the Cancer Moonshot. To Lane, that overlap is a formula for bureaucratic confusion, if not gridlock. “Who’s in charge?” he asks. “If Francis isn’t reporting to Alondra, that raises serious questions.” Lane also worries that some senior administration officials might regard Nelson as Collins’s deputy, while Collins assumes a more visible public role. Holdren disagrees. He thinks bringing in Collins will bolster the White House science team. “Biden wanted someone of stature in biomedical research to lead the charge [on his priorities], and that is what Francis Collins represents,” Holdren says. “Lander was doing that. But those issues are not in Alondra Nelson’s wheelhouse.” Biomedical research advocates are also divided over the appointments. Collins’s long government tenure and easy rapport with Congress make him an ideal candidate to push the health initiatives forward, says Ellen Sigal, founder and chair of Friends of Cancer Research. “There’s no one better than Francis,” she says. At the same time, many lobbyists are unhappy with the administration’s intent to house ARPA-H within NIH, a plan Collins has backed. They would prefer to see it have more independence by locating it within NIH’s parent body, the Department of Health and Human Services. And several researchers complained about the Biden administration opting for yet another “old white dude” to be science adviser, reviving a criticism levied when Lander was named. Neither Collins nor Nelson will get Lander’s Cabinet seat. Science advocates applauded Biden’s decision to elevate the OSTP director to the Cabinet, a status normally held by heads of major agencies who are Senate-confirmed. But an OSTP spokesperson says whoever Biden nominates for the permanent position will have Cabinet status once confirmed. j With reporting by Jocelyn Kaiser. SCIENCE science.org

Archaeologists and fieldworkers excavate Malawi’s Hora rock shelter, where two male infants had been buried.

HUMAN EVOLUTION

Oldest genomes from Africa offer glimpse of complex past Signs of ice age isolation match archaeological clues By Michael Price

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frica is the birthplace of our species, but ancient DNA from the continent has so far provided relatively few clues to our history there, partly because researchers have struggled to recover genetic samples that survived the hot, humid climate. Now, an analysis of ancient DNA from six individuals from southeastern Africa offers a glimpse of the lives, movements, and relations of people who occupied the continent between 18,000 and 5000 years ago; it also hints at the complex commingling of African populations even further back. For instance, the work suggests that during the last ice age, some African societies may have become more sedentary and isolated as their environments fragmented. The study, published this week in Nature, is “terrific,” says Susan Pfeiffer, an anthropologist emeritus at the University of Toronto. “It’s like a little hint of what I hope will be a wonderfully rich story.” To get a clearer picture of ancient Africa, a team led by North American researchers and including 13 scientists from five African nations analyzed samples from the remains of four infants and two adults buried in Malawi, Tanzania, and Zambia. The team managed to extract enough DNA to partially

sequence the genomes. Five samples came from inner ear bones, which are dense and preserve DNA well. Two infant boys from the Hora rock shelter in Malawi were buried on their sides in a flexed position about 14,000 years ago. “I spent a lot of time thinking about the circumstances that led to them dying so young and … about how carefully their communities had interred them,” says Yale University anthropologist Jessica Thompson, who led the Hora excavation in 2019. The most recent remains, of an adult woman from Zambia’s Kalemba rock shelter, were radiocarbon dated to about 5000 years ago. The oldest remains belonged to a woman found in Tanzania’s Mlambalasi rock shelter amid ostrich eggshell beads radiocarbon dated to about 18,000 years ago. Previously, the oldest human genome from sub-Saharan Africa was 9000 years old. Thompson and colleagues analyzed the six new partial genomes plus 28 previously reported from across the continent. The team ran the data through a computer program that compares similar snippets of DNA to estimate relatedness; they reconstructed a rough family tree dating back 18,000 years. Their model suggests the 34 individuals descend from three major source populations. Two of them, from northeastern Africa and southern Africa, were already known. 25 FEBRUARY 2022 • VOL 375 ISSUE 6583

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But the third population, from Central Africa and most closely related to people today who live a foraging lifestyle there, came as a surprise. The distinct genetic signatures of those ancestral populations indicate they were mostly isolated from one another for vast amounts of time before eventually coming together, suggests David Reich, a population geneticist at Harvard Medical School who co-led the study. “If you look at Europeans and East Asians, maybe they’re separated by 40,000 or 50,000 years,” he says. “These three groups were basically separated 200,000 years ago, then come together … maybe 80,000 to 50,000 years ago.” That range is only a rough estimate, Reich notes, given none of the new genomes dates beyond 20,000 years ago. But that time frame for commingling matches developments in material culture, says co-author Mary Prendergast, an archaeologist at Rice University. In African artifacts of that period, “we see a ton of hints that people are connecting in different ways,” she says, mixing and matching artifacts from distant places. Considered in that context, the new DNA data suggest sometime after 20,000 years ago, ancient Africans stayed closer to home. Stone tools found in their rock shelters take on a local flair. And their DNA suggests that starting around this time, people traveled shorter distances to find mates. That date range marks the Last Glacial Maximum, which affected climate worldwide, points out Rick Potts, a paleoanthropologist at the Smithsonian Institution’s National Museum of Natural History. Across tropical Africa, forests contracted and grasslands grew in between, forming fragmented savannalike “islands” for many species—perhaps humans among them. “It’s interesting to think about whether sub-Saharan African foragers were mapping onto a kind of refugium model.” The six new genomes are a welcome addition to Africa’s sparse record of ancient DNA, says Sarah Tishkoff, a geneticist at the University of Pennsylvania. But she’s not swayed by the team’s ideas about what happened before 20,000 years ago. “There’s a lot of assumptions in that analysis,” she says, and it’s not clear to her that the authors considered alternative explanations. The analysis included some remains from museums, highlighting the key role of collections, says study co-author Maggie Katongo, a curator at Zambia’s Livingstone Museum and a doctoral student at Rice University. “When you do this research, you want to give back to the community,” she adds. “We want to make sure that whatever comes from this research is made public for all people in Zambia.” j 804

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BIOMEDICINE

Glowing tumor marker hampers mouse cancer studies Response to protein complicates immunotherapy research By Jocelyn Kaiser

But as immunotherapies have taken off in the past decade, more labs are working ancer biologist Cyrus Ghajar was with mice that have intact immune sysgearing up to study how the immune tems. Ghajar and others shifted to mouse system can fight breast cancer when cancer cells, which aren’t immediately rehe hit a snag: The supposedly fastjected. Others use mice that have humanspreading cancer cells he implanted in ized immune systems and accept human mice stayed put and sometimes even cancer cells. disappeared after about 11 days. Then, postGhajar’s lab realized its mice were prodoc Candice Grzelak identified the culprit: ducing immune sentinels called T cells the green fluorescent protein (GFP) the rethat attacked the GFP-labeled cells, blocksearchers were using to track the cells. The ing their growth. They lowered the levels of marker itself was stimulating the rodents’ imGFP, but the cancer cells still didn’t metasmune system to attack the tumor cells. tasize. The group found the best solution Ghajar’s lab at the Fred Hutchinson was to trick the mouse immune system into Cancer Research Center got around this thinking the GFP was a natural protein, by unexpected problem, which using mice engineered to it described in a paper last produce GFP in certain immonth. But he and othmune cells known as deners say the experience redritic cells, which induce flects a broader issue in tolerance. In these rodents, mouse studies of immunothe breast cancer cells grew therapies, treatments that as expected, they reported harness the immune sysin Cancer Cell. tem to vanquish tumors: “We wanted to draw atThe glowing proteins biotention to the problem and logists use to track the canprovide the field with recer cells, often borrowed agents and metrics necesfrom fireflies or jellyfish, sary to solve it,” Ghajar says. may provoke their own imMerlino and his coCyrus Ghajar, mune attack on the cells. authors warn in their comFred Hutchinson Cancer Other foreign proteins mentary that the same Research Center that are workhorses of lab problematic immune restudies, such as components of the genome sponse could arise in experiments using editor CRISPR, could have the same effect. other glowing proteins from various speAnd the phenomenon could explain why labs cies, viral proteins that cause cancer, and sometimes can’t reproduce immunotherapy even Cas9, CRISPR’s DNA-cutting enzyme, findings from other groups, suggests Glenn which comes from a bacterium. ResearchMerlino, a cancer biologist at the National ers may need to find workarounds, such Cancer Institute. as mouse strains modified so they tolerate As immunotherapy becomes more and the foreign proteins, like the mice turned more important, he adds, scientists need to to by Ghajar’s lab. Merlino calls for other be aware of confounding factors like this. “So researchers to share similar experiences, many preclinical experiments do not end up perhaps in a database. telling you anything useful in the clinic,” says Peter Friedl, who studies metastasis at Merlino, a co-author on commentary on the Radboud University and the MD Anderson issue last week in Cancer Cell. Cancer Center, says he, too, has had experiAlthough it’s long been known that the ments fail because of an immune reaction immune system can sense marker proteins to a nonmouse marker protein. Researchsuch as GFP as foreign, it didn’t much matter ers have fingered other causes for cancer for cancer studies. That’s because most labs biology’s replication problem, such as variused mice lacking an immune system so they ations in mouse colony microbiomes. But would not reject the transplanted human the unexpected immune responses, Friedl cancer cells often used to assess treatments. says, “absolutely” could contribute. j

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“We wanted to draw attention to the problem and provide the field with reagents and metrics necessary to solve it.”

science.org SCIENCE

Raccoon dogs in China were found to harbor several novel coronaviruses.

COVID-19

Novel viruses highlight risks of Asia’s wild animal trade Sampling of game in China reveals many viral threats By Jon Cohen

PHOTO: SU SHUO

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ild animals that are sometimes on the menu in China harbor a bewildering panoply of viruses, including many novel ones that may be able to infect humans, a study published in Cell on 16 February has found. Although none is closely related to the coronavirus that caused the COVID-19 pandemic, the study sends a clear warning that other viral threats are lurking in the animal kingdom, scientists say. “There is an enormous amount of unsampled viral diversity” in animals, says Harvard University evolutionary biologist William Hanage, who was not involved in the work. “We humans need to understand that for a virus, different mammal species can look pretty alike, provided their cells have appropriate receptors.” Live-animal markets are known to have sparked outbreaks, such as severe acute respiratory syndrome (SARS) 2 decades ago. China has since clamped down on the sale of the animals sampled in the study, but other countries in the region have not. The researchers, led by veterinarian Su Shuo of Nanjing Agricultural University, took samples from nearly 2000 animals representing 18 different species at fur farms, zoos, and natural habitats in China. Most were species traditionally eaten as delicacies in SCIENCE science.org

China, including civets, raccoon dogs, badgers, bamboo rats, and porcupines. Using a “metagenomics” technique, which probes samples for RNA transcripts that viruses make when they copy themselves, they identified 102 virus species from 13 different viral families in the animals’ noses, feces, and tissues. The researchers deemed 21 of those as “high risk” to humans, because they had infected people in the past or had a history of readily jumping between species. Sixty-five viruses had never been described before. “Our results provide important insights to those game animals and their viruses that might lead to the next pandemic,” Su says. Among the worrisome finds were several coronaviruses. For example, a hedgehog was infected with a virus resembling the one that causes Middle East respiratory syndrome in humans. Four canine coronaviruses found in raccoon dogs were about 94% similar to coronaviruses recently found in humans in Malaysia and Haiti. “These viruses can infect many animals,” Su says. Some of the sampled species could act as intermediary hosts that bat coronaviruses infect before they make the jump to humans. Indeed, a coronavirus close to one found in bats turned up in a civet. Most researchers think both SARS-CoV-2 and SARS-CoV-1—the cause of SARS—became human pathogens after passing through an intermediate host.

The researchers also detected several influenza viruses, another family that could trigger a new pandemic. In a finding “of considerable significance,” they write, civets and Asian badgers carried H9N2, an influenza A virus that has become increasingly common in chickens and ducks. H9N2 does not transmit efficiently between people and a February 2020 report noted that fewer than 50 human infections have been documented. But researchers fear that the virus, by replicating in other mammals, has more opportunities both to infect humans and to adapt to them. The infected badgers had runny noses and presumably could transmit to humans through the respiratory route. Other viruses detected in the study that can infect people include influenza B, Norwalk, human parainfluenza virus 2, rotaviruses, and orthoreoviruses. Markets that sell live animals—often called “wet markets”—are ideal places for viruses to transmit to humans, both because of the density of animals and because the stress they suffer makes them prone to shedding viruses, says medical virologist Marietjie Venter of the University of Pretoria, Hatfield. The new findings “confirm that trade and consumption of these animals should be avoided and support the actions taken by China to ban the trade of many of these animals,” says Venter, who is a member of the World Health Organization’s Scientific Advisory Group for the Origins of Novel Pathogens. After SARS, China made the sale of many of the animals sampled in the study illegal, but they were still readily available in Wuhan markets in 2019, just before the start of the pandemic, including at the Huanan Seafood Market, which had the earliest identified cluster of COVID-19 cases. Su says the government has cracked down hard on illegal sales since then. “With very strict legislation, as well as screening checks, it is now difficult to find wildlife” for sale, Su says. “What worries me is that it seems that in Southeast Asia, where the economy is lagging, this wild animal trade is continuing.” Evolutionary biologist Edward Holmes at the University of Sydney, a co-author of the new study, “strongly suspects” SARS-CoV-2 jumped into humans at the Huanan market. As long as wild animals are sold, the risk of other viruses making a similar jump is high, he says. “It’s hard to think of a more effective way to ignite and fan the flames of an epidemic,” Holmes says. “We keep allowing these things to flourish and it’s only a matter of time before we get another outbreak and perhaps another pandemic.” j 25 FEBRUARY 2022 • VOL 375 ISSUE 6583

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NEWS

FINAL RESTING PLACE Finland is set to open the world’s first permanent repository for high-level nuclear waste. How did it succeed when other countries stumbled? By Sedeer El-Showk

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fter passing through a security gate, the van descends into a tunnel that burrows under the forests of Olkiluoto, an island off Finland’s west coast. The wheels crunch on crushed stone as a gray, wet October day gives way to darkness. “Welcome to Onkalo,” deadpans Antti Mustonen, a geologist here. Onkalo—“cavity” or “pit” in Finnish—will be the world’s first permanent disposal site for high-level nuclear waste, and a triumph for Finland. Safety lights guide the van down through switchback turns that lead to a cavernous chamber, its walls reinforced with spray-on concrete. In just a few years, spent reactor fuel rods, encased in giant copper casks as tall as giraffes, will arrive here via elevator before robotic vehicles take them to one of the dozens of dead-end disposal tunnels that will form an ant’s nest in the bedrock. In a freshly excavated disposal tunnel, Mustonen explains over the roar of ventilator fans that the peculiar smell comes from rock dust mixed with a trace of explosives. It is muddy underfoot—not what you want to see in a place that shouldn’t have leaks, but Mustonen says the water is only from the excavation effort. In the blackness, bare bedrock glints in the meager light from the van. After 30 to 40 of the copper casks are buried in the tunnel floor, the holes will be plugged with bentonite, a water-absorbing clay. Each tunnel will be backfilled with more bentonite and sealed with concrete. The casks will then begin their long vigil. They must remain undisturbed for 100,000 years, even as the warming climate of coming centuries gives way to the next ice age. “It’s final disposal,” Mustonen says. “Right here, in stable Finnish bedrock, 430 meters belowground, 420 meters below sea level.” Although nuclear power is declining in many nations, Finland has embraced the carbon-free energy source, lobbying the European Union to label it as sustainable. Two of the country’s four reactors are on Olkiluoto. After a new Olkiluoto reactor is connected to the grid later this year, nuclear power will account for more than 40% of Finland’s electricity. The emissions-free electricity comes with a downside: hot and highly radioactive spent uranium fuel rods. In Finland, the rods cool for decades in pools of water; other nations park them in concrete and steel “dry storage” casks. Either way, surface storage is vulnerable to accidents, leaks, or neglect during the thousands of years the

About 100 nuclear waste disposal tunnels are being dug 430 meters underground at Onkalo. SCIENCE science.org

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waste remains dangerous, says Budhi Sagar, a nuclear expert formerly at the Southwest Research Institute. “It’s not safe—some disaster will occur,” he says, citing the groundwater contaminated by leaky waste tanks at the U.S. Department of Energy’s (DOE’s) Hanford Site in Washington state, where reactors produced plutonium for the first nuclear weapons. Without a long-term solution, the waste is piling up. Finland had about 2300 tons of waste in 2019, and about 263,000 tons of spent fuel sit in interim storage facilities worldwide, a report this year from the

led to conflict rather than cooperation.” Finland, however, has run into remarkably few problems with Onkalo, which the government approved as a site in 2000. It helped that the residents of Eurajoki, the town closest to Onkalo and the nearby reactors, were comfortable with nuclear power. “Almost everyone in Eurajoki has a friend or relative who has worked in the nuclear power plants, so they know how we operate,” says Janne Mokka, CEO of Posiva, the nuclear waste company set up by two nuclear power utilities to develop and manage Onkalo. But experts say the success of Onkalo

Spent uranium fuel rods will be sealed within thousands of tall, corrosion-resistant copper canisters.

International Atomic Energy Agency estimates. “In my view, that’s an unacceptable legacy to leave to future generations,” says Tom Isaacs, a strategic adviser for Canada’s Nuclear Waste Management Organization (NWMO) and Southern California Edison. “We generated this electricity. We benefited from that.” Many experts view permanent deep repositories like Onkalo as the best solution, but getting community buy-in is often a deal breaker. Street protests have slowed down plans for a disposal site in France, and in 2009, after years of debate, then-President Barack Obama’s administration gave up on plans to develop Nevada’s Yucca Mountain as the U.S. national repository. “The U.S. approach didn’t pay sufficient attention to community acceptance or engagement,” says Isaacs, who was the lead adviser on a 2012 blue-ribbon report commissioned by DOE to chart a way forward. “The original approach

also reflects unique cultural and political conditions in Finland: high trust in institutions, community engagement, a lack of state-level power centers, and a balance of power between industry and stakeholders. “If you tried to implement the same thing in a country with much lower levels of trust, it would probably fail,” says Matti Kojo, a political science researcher at Tampere University in Finland. “The Finns have been able to articulate a consistent message about what they’re doing, why they believe this facility will be safe, and why it will be a major benefit to the wellbeing of certain communities,” Isaacs says. In late December 2021, Posiva applied for a license to begin operations in 2024. POSIVA BEGAN its search in the 1990s, with

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between Olkiluoto and the area around the town of Loviisa, which houses the country’s other nuclear power plants. In 1999, Posiva put forward the site that would become Onkalo. The bedrock at Onkalo has been mostly stable for the past billion years, geologists say, although there is evidence of earthquakes during the past 10,000 years as massive glaciers retreated at the end of the last ice age and the bedrock rebounded. Posiva scientists don’t expect significant earthquakes in the region until after the next ice age. Mustonen says Onkalo was purposefully situated between two parallel fault zones about 800 meters apart. If an earthquake were to occur, it would preferentially happen along those existing fault lines, he says. “They absorb the movement and nothing happens here in the area in between.” But earthquakes aren’t the main threat. “The only way for things to move from the repository out to the surface and to impact people is to be carried by water,” says Sarah Hirschorn, director of geoscience at NWMO. That means deep repositories are best situated in certain types of clay, salt, or hard crystalline rock, because they have small, disconnected pore spaces and are almost impermeable to water. At Onkalo, the nearly 2-billion-year-old bedrock is mostly gneiss, a hard rock formed at high temperatures and pressures. Although decidedly nonporous, these rocks can still contain cracks, and Posiva had to map and avoid them as workers dug deeper. “It’s these fractures which control the movement of water,” says Neil Chapman, a geologist who has served as an 808

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independent consultant for Finland’s nuclear regulator, the Radiation and Nuclear Safety Authority (STUK). If any significant fractures are discovered when drilling individual cask pits, he says, those holes won’t be used. If water were somehow able to seep into the repository, it would still have to get past the bentonite and copper to reach the spent fuel. “You’re never relying on a single barrier,” says Emily Stein, who researches deep geologic disposal at DOE’s Sandia National Laboratories. “If one barrier fails, you have other barriers that can minimize or prevent radionuclide release.” After arriving at Onkalo, spent fuel will be unpacked in an encapsulation plant. In a stainless steel room surrounded by 1.3-meter-thick concrete walls, robots will vacuum away any water left on the fuel rods from their time in the storage pools, and seal them within a cast-iron canister nested inside a copper canister. Argon will be injected between the two canisters to provide an inert atmosphere, and the copper cask will be welded shut. Copper is slow to corrode, and by the time any groundwater does reach Onkalo’s depths, chemical or microbial reactions would have consumed all of its dissolved oxygen, making it less reactive. But Peter Szakálos, a chemist at the KTH Royal Institute of Technology in Stockholm, has concerns. In a 2007 study, he and colleagues found signs that copper can corrode even in pure, oxygen-free water. When the metal is exposed to water, Szakálos and his colleagues found it releases a whiff of hydrogen gas. He suspects the water reacts with the

copper to form a “distorted” copper oxide crystal along with free hydrogen, which is either released or absorbed into the copper. Szakálos says any absorbed hydrogen would make the copper brittle and prone to cracking, and bronze would have been a safer choice. “It’s just a matter of time—between decades and centuries—before unalloyed copper canisters start to crack at Onkalo.” Posiva and SKB, Sweden’s nuclear waste management company, say Szakálos’s experimental conditions are not relevant for the planned repositories. Even so, SKB contracted Uppsala University and the University of Toronto to try to replicate the findings. The Uppsala tests did not find evidence of any reaction with pure water, whereas the Toronto group observed one but said it was too slow to matter. “Making a measurement that tells you nothing happened is impossible,” says David Shoesmith of the University of Western Ontario, a corrosion chemist who has consulted for SKB. “Based on what’s been published, the answer to this question is that minimal things will happen.” Those concerns nevertheless delayed plans for what would be the world’s second deep repository, near the Swedish coastal town of Forsmark. In 2018, Sweden’s Land and Environment Court called for SKB to provide more evidence that copper corrosion would not undermine long-term safety. SKB submitted additional documentation to the Swedish Radiation Safety Authority, and in January, the Swedish government approved the facility based on the regulator’s assessment that the other barriers would keep the repository safe.

PHOTO: TAPANI KARJANLAHTI/TVO

Spent fuel rods from Olkiluoto’s nuclear power plants will cool off for several decades in interim storage pools before final burial at Onkalo.

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In addition to the casks themselves, the bentonite surrounding them will also prevent radionuclide escape, regulators say. The mineral not only keeps water away, but also prevents microbes from reaching the canister surface. Microbes can pose a threat, says Karsten Pedersen, CEO of Microbial Analytics Sweden, a company that researches their effect on deep repositories, because they can metabolize sulfates in groundwater and turn them into sulfides, which can slowly corrode copper. Posiva acknowledges that possibility, but the company’s calculations suggest that even at elevated sulfide levels, the canisters would have a lifetime of more than 100,000 years. Should all these barriers fail, escaping waste would face one last impediment: the decades it would take to migrate to the surface, with radioactivity levels dropping all the while. Sagar, who reviewed the longterm scenarios that were a part of STUK’s overall safety assessment, says that even under worst-case assumptions the impact of leaking radionuclides would be minimal. For people living near the repository and drinking contaminated water from deep wells, the assessment found, the annual exposure would be well below the allowable limit set by STUK, which is about the same as the average background radiation exposure a person in Finland experiences today. “That’s the point of a multibarrier system,” Sagar says. “Even if some containers fail or a systematic construction error means they all have defects, the geology and other barriers are good enough that you’re still within limits.”

Nuclear necropolis In just a few years, workers plan to entomb high-level nuclear waste at Onkalo, a repository on the Finnish island of Olkiluoto that is meant to store spent fuel rods for 100,000 years. The waste will be buried in about 100 tunnels 430 meters belowground. Onkalo relies on multiple barriers to prevent water from reaching the rods and carrying radionuclides to the surface.

SCIENCE science.org

GRAPHIC: V. ALTOUNIAN/SCIENCE

FINLAND 430 m Olkiluoto

Time capsules Onkalo is carved out of gneiss and granite, two hard, crystalline rocks that are nearly impervious to water. If workers encounter any fractures during the excavation of a disposal pit, it won’t be used. Once filled, disposal tunnels are backfilled and sealed.

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Bentonite backfill

Fuel rods

YET THE TRUE SECRET to Finland’s success

with Onkalo lies not so much in geology and engineering, but in the site selection process, the structure of government, and a culture of trust in institutions and expertise. Finland’s 1987 Nuclear Energy Act set up a nuclear waste management fund, financed by the nuclear operators, which incentivizes companies to develop waste disposal solutions. It also insulates the process from politics. Isaacs notes how this differs starkly from the situation in the United States, where DOE—which answers to the White House—runs the waste disposal program. “No matter how competent and wellintentioned people are, presidential and congressional elections are held regularly,” he says. Important decisions can end up subject to political expedience, crippling a project that takes decades to build. Another important difference, according to Isaacs, is the absence of strong statelevel government in Finland. State governments, often far from disposal sites, see repositories more in terms of perceived

SWEDEN

Argon gas

Spent fuel rods of enriched uranium are sealed within shells of iron and copper. Inert argon gas is injected between the two metal shells.

Iron

Copper The metal was chosen because it is malleable, weldable, and unreactive in oxygen-free waters, although some scientists say corrosion might still be possible in pure water.

Bentonite An outer shell of bentonite, an absorbent clay, serves as another barrier to water. It also keeps out microbes, which can create sulfides, another possible pathway to copper corrosion.

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Onkalo’s encapsulation plant (white) sits atop an ant’s nest of underground tunnels in this August 2021 photo. Olkiluoto’s nuclear power plants can be seen in the distance.

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ized it would have to engage more and build local political support using an approach Kojo calls “mitigate-understand-mediate.” Once an agreement was reached, Eurajoki residents were largely willing to leave technical matters and safety questions to expert bodies. “In Finland, there is a very high level of trust in science and in the authorities,” Kojo says. “If the national authority says the repository is safe, they don’t need to worry about it.” The process became a purely technocratic affair in the hands of Posiva and STUK. Not everyone’s concerns have been allayed. The Finnish Association for Nature Conservation (FANC) says it is worried about long-term ecotoxicity and bioaccumulation of the radioisotopes. It also cites concerns raised by retired geologist Matti Saarnisto, former director of research for the Geological Survey of Finland. In 2010, Saarnisto told Finland’s national broadcaster that as the next ice age arrives, freezing soil and rock could create pressures that would damage the repository. In any case, Saarnisto argued, it is impossible to make predictions on the scale of 100,000 years. Jari Natunen, a scientist with FANC, says the relationship between industry and regulators in Finland is far too cozy—a form of “structural corruption.” “The authorities are biased to think that the industry’s position is correct and valuable, and the concerns of civil society are not,” says Natunen, who is also a member of Nuclear Transparency Watch, an antinuclear advocacy organization. Natunen adds that the Finnish media’s

coverage of Onkalo has been too compliant. By contrast, in the United States, France, and Sweden, safety concerns remain a central part of the public debate. A 2020 study by Kojo and his colleagues, for example, found that France’s Le Monde newspaper played a more critical role in debates about repositories, acting as a watchdog that challenged authorities, whereas Finland’s leading daily, the Helsingin Sanomat, generally took a more positive approach that reflected the framing and confidence of the government and industry. If getting the operating license goes smoothly, Posiva is on track to begin to bury nuclear waste deep in the Finnish bedrock in 2024 or 2025. Excavation will continue over the next century as new disposal tunnels are added. When the repository is filled to capacity, sometime around 2120, the entrance tunnel will be sealed shut. The encapsulation plant and other surface structures will be demolished. Nothing above will remain, not even a warning sign. Deep below the dismantled site, 6500 tons of spent fuel rods will lie in their tombs, quiet but still warm from radioactive decay. “What we are doing really has meaning and is really important,” Mustonen says. “For me, this is the reasonable thing to do with nuclear waste, and we need to make it as good as possible. The sense of responsibility to the next generation doesn’t keep me awake at night, but it’s there. It just is.” j Sedeer El-Showk is a science journalist in Helsinki who joined the communications team at Aalto University at the end of 2021. His reporting was carried out independently.

PHOTO: TVO

costs rather than benefits, Isaacs says. Nevada officials—governors, senators, and others—have consistently opposed the development of the Yucca Mountain facility, blocking funding and throwing up other hurdles. More recently, state politicians in New Mexico have opposed a proposed temporary storage facility for nuclear waste in the state. In Finland, without comparable power centers to play spoiler, Posiva and the national government could deal directly with communities like Eurajoki. Community acceptance was forged in the back and forth between Eurajoki and Posiva, Kojo says. “In the 1990s, the power companies knew that they really needed approval at the local level,” he explains. Finnish law gave Eurajoki the right to veto disposal in the area. But Eurajoki officials were tempted by the tax revenue that would come from the third nuclear power plant if Posiva’s parent company, TVO, decided to build it there. Posiva also funded the construction of a new senior center in town. This approach—continual engagement with potential host communities—is rare in many other countries, including the United States. Even in Finland it is new. In the mid-1980s, Finland had a technical, top-down approach with no public participation that experts like Kojo and Isaacs call “decide-announce-defend.” In 1986, TVO announced it would investigate the municipality of Ikaalinen as a final disposal site. However, local resistance, particularly in the wake of the catastrophic nuclear accident at Chernobyl in the former Soviet Union, foiled the plans. The company real-

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Application Deadline

Tell the World About Your Work! Eppendorf & Science Prize for Neurobiology The annual Eppendorf & Science Prize for Neurobiology is an international prize which honors young scientists for their outstanding contributions to neurobiological research based on methods of molecular and cell biology. The winner and finalists are selected by a committee of independent scientists, chaired by Science’s Senior Editor, Dr. Peter Stern. If you are 35 years of age or younger and doing great research, now is the time to apply for this prize.

June 15, 2022

As the Grand Prize Winner, you could be next to receive > Prize money of US$25,000 > Publication of your work in Science > Full support to attend the Prize Ceremony held in conjunction with the Annual Meeting of the Society for Neuroscience in the USA > 10-year AAAS membership and online subscription to Science > Complimentary products worth US$1,000 from Eppendorf > An invitation to visit Eppendorf in Hamburg, Germany It’s easy to apply! Write a 1,000-word essay and tell the world about your work. Learn more at:

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AAAS® and Science® are registered trademarks of the American Association for the Advancement of Science, USA. Eppendorf® and the Eppendorf Brand Design are registered trademarks of Eppendorf SE, Germany. All rights reserved, including graphics and images. Copyright © 2022 by Eppendorf SE. Photography: Happy Hour Headshot Philadelphia.

2021 Winner Amber L. Alhadeff, Ph.D. Monell Chemical Senses Center, USA For research on the gut-brain control of hunger circuits

2/18/22 9:29 AM

INSIGHTS

FILM

Science at Sundance 2022 Conceived of as a hybrid event during a period of pandemic optimism, the 2022 Sundance Film Festival pivoted at the last minute from partially in-person to fully online—a move that likely caused chaos behind the scenes but didn’t faze our panel of virtual festival-goers. From a vivid documentary on the late volcanologists Maurice and Katia Krafft, featuring stunningly restored volcanic footage captured by the pair, to a melancholic meditation on the roles that social robots may soon play in our lives and families, this year’s program featured a number of films with strong science, engineering, and technology themes. Read on to see what our reviewers thought of six of this year’s offerings. —Valerie Thompson

To The End Reviewed by Sarah Roth1 To The End, directed by Rachel Lears, traces the latest push to pass historic climate legislation in the United States amid record-breaking natural disasters, a global pandemic, and a racial justice reckoning. It follows a trailblazing 812

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group of young climate activists as they work to advance both climate and social policy.  The story picks up where Lears’s 2018 film, Knock Down the House, left off, documenting the buzz surrounding the policy document known as the Green New Deal, which put forward a blueprint for reaching net-zero carbon emissions by 2030 while fueling job growth and investment in disadvantaged

communities. In the words of congresswoman Alexandria Ocasio-Cortez: “The climate and environment piece is what we need to do, the justice and equality piece is how we do it.” The film weaves together the stories of three young women of color—Varshini Prakash of the youth-led “Sunrise movement,” Alexandra Rojas of the progressive political action committee Justice Democrats, and Rhiana GunnWright, policy director of the think tank New Consensus and coauthor of the Green New Deal—documenting their efforts to challenge a political system that favors the status quo along with their private moments of doubt and frustration. We witness these young activists and their collaborators soberly describing the stakes of the climate emergency, campaigning to elect progressive legislators, confronting elected officials, and even participating in a harrowing near-fatal hunger strike. The film concludes at the end of 2021, when hopes run high for major climate legislation in the form of the Build Back Better bill. In congressional hearings and political debates, opponents argue that the bill is too costly. But graphic scenes throughout the film force viewers to confront the enormous costs associated with not addressing climate change.  As the fate of this legislation rescience.org SCIENCE

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mains uncertain, the activists’ expressions of anxiety and hope make clear that much work remains to be done.  Some of the film’s most compelling moments emerge against the backdrop of archival footage documenting the rise of the New Deal out of the economic devastation of the Great Depression and the US mobilization to defeat fascism during World War II. Such scenes remind us that the social contract between Americans and their government has been rewritten before and can be again. The views expressed herein are the author’s own and do not necessarily reflect the opinions of the Environmental Law Institute.

To the End, Rachel Lears, director, Jubilee Films, 2022, 103 minutes.

All That Breathes Reviewed by Amit Chandra2 In a working-class neighborhood of New Delhi’s Muslim quarter, two brothers work tirelessly to rescue and rehabilitate local birds of prey. Winner of Sundance’s World Cinema Grand Jury Prize: Documentary, All That Breathes paints an engrossing portrait SCIENCE science.org

of the siblings and the city’s wildlife as they endure environmental and political turmoil. Toxic air, poor visibility, and collisions with buildings and electrical wires make bird injuries a common occurrence in New Delhi. Brothers Nadeem Shehzad and Mohammad Saud began their journey into wildlife conservation in 2003, when they brought an injured black kite (Milvus migrans) to a local bird hospital, only to discover that the facility was unable to treat it. (The hospital, operated by vegetarian adherents of the Jain faith, refused to treat meat-eating animals.) The brothers returned home and cared for the bird themselves, building a makeshift infirmary in a basement that doubles as a factory for their soap dispenser business. They have since treated more than 20,000 birds. Director Shaunak Sen captures the remarkable intimacy that exists between the two brothers as their informal search and rescue service becomes the primary focus of their lives. The pair invest the bulk of their assets into this activity, which they clearly see as crucial to their own survival. Meanwhile, long takes show viewers how the megacity in which the brothers’ story is unfolding teems with life—a turtle crawls across plastic garbage, a snail crosses a busy street, a majestic

bird glides effortlessly across the sky. These moments bring serenity and a wide lens to the drama surrounding the film’s human and animal subjects. The wildlife and the brothers alike serve as witnesses to the toxic accumulation of pollution in the city’s air, water, soil, and even local politics. “Delhi is a gaping wound and we’re a Band-aid on it,” laments Shehzad. And yet they persevere. As political tensions rise and riots erupt in the city around them, the brothers press on with their mission, propelled by new grant funding secured after their efforts are featured in the New York Times. The pair’s delicate equilibrium is tested when Shehzad is invited to study animal rescue in the United States, an opportunity Saud initially resists but embraces by the end of the film. The film’s message is timely against the accelerating effects of pollution and climate change. Our fate is intertwined with the planet’s biodiversity, insist the brothers. Quoting their deceased mother, they maintain that “we should not differentiate between all that breathes.” All That Breathes, Shaunak Sen, director, Rise Films, 2022, 91 minutes. 25 FEBRUARY 2022 • VOL 375 ISSUE 6583

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After Yang Reviewed by Lindsey Brown3 Winner of the 2022 Alfred P. Sloan Feature Film Prize, After Yang, directed by Kogonada, is based on a short story with a very simple premise: the family robot, Yang, has unexpectedly broken. In the film, patriarch Jake (Colin Farrell)—a pensive tea purveyor—undertakes the task of getting Yang (Justin H. Min) fixed while his wife, Kyra (Jodie TurnerSmith)—the family breadwinner—is busy with work. Meanwhile, the couple’s daughter, Mika (Malea Emma Tjandrawidjaja), for whom Yang was originally acquired, misses her best friend. Purchased refurbished when Mika, now in elementary school, was an infant, Yang is a “technosapien,” designed to serve as a tool for linking Chinese children adopted into Western families with their cultural heritage. After a certified repair shop declines to fix Yang, Jake secures the services of an unauthorized repairman, who suspects that the android has been equipped with spyware. Jake then takes Yang to the Museum of Technology, where curator Cleo (Sarita Choudhury) accesses a file filled with thousands of brief video clips captured by Yang throughout his time with the family. The robot’s “memories” include his initial interactions with baby Mika, snippets from his life as her caretaker, and seemingly mundane moments such as taking a family photo— perspectives that sometimes contrast with the family’s memories of Yang. As Jake views the videos and reflects on his relationship with Yang, he notices the recurring appearance of a mysterious young woman. A deeper investigation reveals that

Yang’s interior life was far richer than Jake had imagined. In the film’s not-too-distant future, there have been many technological advances in the aftermath of an unspecified climate disaster: self-driving cars seem to be the norm, one can watch videos via eyeglasses, and human clones and biological robots are not uncommon. Far from a flashy, futuristic dystopia, however, After Yang is lush and quiet. Advanced technologies—some of which raise questions about the very nature of humanity—are all but invisible in the film, seamlessly woven into everyday life. After Yang’s distinctive perspective on the human experience prompts reflections on loss and grief and invites viewers to consider their connections to technology. It also asks unexpected questions: What are memories, if not simply a record of time? How are our identities formed and shaped? Are there patterns to the rules of attraction? Such queries, we learn, often have complex answers. The views expressed herein are the author’s own and do not necessarily reflect the opinions of the US Food and Drug Administration.

After Yang, Kogonada, director, A24, 2021, 96 minutes.

The Territory Reviewed by Gabrielle Kardon4 In The Territory, directed by Alex Pritz, the Amazon is under siege. Motorcycles roar through the underbrush, chainsaws and fires demolish large swaths of trees, and the threat of violence is ever present. At the center of this conflict are 7000 square miles of rainforest, home of the Indigenous Uru-

Before he malfunctions, android Yang (right) serves as a cultural link for adoptee Mika (left) in After Yang.

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eu-wau-wau people and the illegal settlers and non-native farmers intent on seizing this land. The film, coproduced with the Uru-eu-wau-wau, is a riveting vérité-style documentary with unparalleled footage of the tinderbox that has been set aflame in Brazil. Since they were first contacted in 1981, the Uru-eu-wau-wau have dwindled to less than 200 people. To survive, they must safeguard the rainforest that is not only their home but also the source of traditional foods and medicinal plants. Although the Uru-eu-wauwau have been granted sovereignty over the disputed region, illegal deforestation and land theft have gradually chipped away at their territory. The film follows 19-yearold Bitaté as he is elected by the Uru-euwau-wau elders to lead them through the current conflict. Environmental activist Neidinha Bandeira plays an essential role as well, publicly admonishing intrusions into the protected area. Together, they brave violent threats and use drones and cameras to document incursions and deforestation. The film also follows a group of farmers organized as the Association of the Rio Bonito, who see themselves as pioneers. In their view, building their own farms is their only means to escape poverty. The association, which has since disbanded, endeavored to establish guidelines to stake legal claims on the areas they clear. However, others—emboldened by the aggressive antienvironmental and anti-Indigenous rhetoric of President Jair Bolsonaro—operate clandestinely. Startling footage shows settler “Martin” setting fire to the forest, for example, an act he views as a way to “liberate” the land. When the COVID pandemic begins, the Uru-eu-wau-wau retreat deeper into the forest. With recording equipment provided by Pritz, Bitaté and the Uru-eu-wau-wau start their own media team and take over filming, documenting confrontations with invaders and discovery of illegal settlements. Their footage provides a singular view of the conflict that they have begun to use to rally public support for the protection of Indigenous lands. The Territory, which received an Audience Award and a Special Jury Award at Sundance, is a tightly edited documentary that explores the intimate relationship between people and land and captures the perspectives of each of a heated conflict’s protagonists. It is also a testament to the power that film can have on environmental action and the protection of Indigenous peoples. The Territory, Alex Pritz, director, Documist, 2022, 86 minutes. science.org SCIENCE

PHOTO: CARA HOWE/COURTESY OF A24

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Striking footage brings Katia and Maurice Krafft’s passion for volcanoes to life in Fire of Love.

Fire of Love

PHOTO: COURTESY OF SUNDANCE

Reviewed by Gabrielle Kardon4 Two foil-clad figures dance incongruously in front of plumes of fiery lava in a scene that epitomizes the striking footage at the heart of the new documentary Fire of Love. Directed by Sara Dosa, the film showcases newly available archival recordings of volcanic eruptions captured by the late volcanologists Katia and Maurice Krafft, giving viewers a glimpse into their lives and their mutual love of volcanoes—a passion that would ultimately kill them. Katia and Maurice came of age during the 1960s—an era that saw antiwar protests and shifting paradigms in the field of geology, the latter heralded by the discovery of plate tectonics and continental drift. In an interview that appears in the film, Maurice highlights how the cultural context of the moment influenced the pair’s trajectory, explaining: “Katia and I got into volcanology because we were disappointed in humanity.” The Kraffts, who both grew up in the Alsace region of France, each cited childhood fascinations with volcanoes as early inspirations for their eventual careers. The pair met at the University of Strasbourg, began exploring volcanoes together in Iceland in 1968, were married in 1970, and soon were traveling the world to visit erupting volcanoes. At each location, they went dangerously close to collect samples and take spellbinding films and photos. Like their contemporary, Jacques Cousteau, the Kraffts cultivated an intrepid public image in which they cast themselves as “wandering volcanologists.” The pair fortified their mythic personas with risky stunts and bold declarations (“I want to get closer, right into the belly of the volcano. It will kill me one day, but that does not bother me at all.”). Fire of Love fully embraces this myth.

Influenced by French New Wave cinema, the film’s narrator, Miranda July, expounds on the existential themes raised by the Kraffts’ love and dangerous obsession. In 1991, Maurice and Katia died together, engulfed by a pyroclastic flow while documenting the eruption of Japan’s Unzen volcano. It is clear from the film that their legacy includes extraordinary footage of a myriad of volcanic eruptions that highlighted the dangers of living near a volcano. But did the pair’s dangerous volcanochasing lead to meaningful scientific contributions? Disappointingly, this fascinating question is left largely unexplored. Fire of Love, Sara Dosa, director, Submarine, 2022, 93 minutes.

Downfall: The Case Against Boeing Reviewed by Lindsey Brown3 The Boeing Company has long been regarded as one of the premier aircraft manufacturers in the world. But when Lion Air Flight 610 and Ethiopian Airlines Flight 302—both flown on Boeing’s newest aircraft, the 737 MAX— crashed within 5 months of one another in 2018 and 2019, killing 346 people, the company’s culture of safety and quality was called into question. Downfall, directed by Rory Kennedy, investigates what caused these tragedies, arguing that Boeing minimized its own responsibility and that it leveraged a campaign of plausible deniability, misinformation, and deception to deflect blame for the crashes. The film’s interviews with pilots, former employees, flight safety experts, legislators, and journalists paint a portrait of a company where safety is no longer paramount. Many of the film’s subjects point to the 1997 merger

with aerospace manufacturing corporation McDonnell Douglas as a time when corporate culture shifted from an emphasis on quality and care to messaging that profit should be prioritized above other considerations. The film documents how, after losing market share to competitors, Boeing produced the 737 MAX, promising airlines that pilots would not require additional flight simulator training to operate the new aircraft. In the aftermath of the October 2018 Lion Air crash, a new feature known as the Maneuver Characteristics Augmentation System (MCAS) was implicated. Boeing initially blamed operator error and promised to implement MCAS training; however, data collected in the wake of the Ethiopian Airlines crash pointed to a critical malfunction of the system. Moved to action by their losses, family members of the crash victims traveled from all over the world to Washington, DC, to pressure the US government to uncover the truth. In one riveting scene, CEO Dennis Muilenburg answers questions from Congress as family members carrying posters with photos of their loved ones look on silently. Court documents would later reveal that Boeing had deceived the US Federal Aviation Administration by omitting crucial information about MCAS from official communications with the agency, and the company agreed to pay more than $2.5 billion under a deferred prosecution agreement. Downfall’s timeline clearly articulates the lead-up to, and fallout from, the 737 MAX crashes—two tragedies that emphasize the importance of prioritizing quality and safety in high-stakes settings. The views expressed herein are the author’s own and do not necessarily reflect the opinions of the US Food and Drug Administration.

Downfall: The Case Against Boeing, Rory Kennedy, director, Netflix, 2022, 89 minutes. 10.1126/science.abo3606

1

Environmental Law Institute, Washington, DC 20036, USA. Email: [email protected] 2Department of International Health, Georgetown University, Washington, DC 20057, USA. Email: amit. [email protected] 3Division of Biotechnology Manufacturing, US Food and Drug Administration, Silver Spring, MD 20993, USA. Email: [email protected] 4Department of Human Genetics, University of Utah, Salt Lake City, UT 84112, USA. Email: [email protected] SCIENCE science.org

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Losing sleep with age

By Laura H. Jacobson1,2,3 and Daniel Hoyer1,2,4

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umans spend approximately one-third of their lives asleep, but this is not distributed equally across their life span. Sleep quantity and quality decline as age advances, and insomnia and sleep fractionation are common in older people (1, 2). Sleep is essential for vitality and health. At any age, chronic sleep deprivation causes a range of issues, including disrupted cognition and memory (3). Correspondingly, sleep complaints in older people are associated with increased risks of impaired physical and mental health and with mortality (4). Beyond evidence of degenerating subcortical nuclei in age-associated sleep disturbances (2), the underlying mechanisms remain unclear despite decades of awareness of the problem and its consequences. On page 838 of this issue, Li et al. (5) report the hyperexcitability of hypocretin neurons as a core mechanism underlying sleep disruption in aged mice, explaining why sleep is punctuated by intruding wakefulness despite the loss of wake-promoting neurons. Hypocretins, neuropeptides that are also called orexins, are produced by a few thousand neurons located exclusively in the lateral hypothalamus. These cells project widely across the brain, providing dense, stimulatory innervation to wake-promoting nuclei, such as the adrenergic locus coeruleus, histaminergic tuberomammillary nucleus, serotonergic raphe nuclei, and basal forebrain cholinergic neurons (6). Hypocretin neurons fire and release hypocretins during 1

Florey Institute of Neuroscience and Mental Health, Parkville, VIC, Australia. 2Department of Biochemistry and Pharmacology, School of Biomedical Sciences, Faculty of Medicine, Dentistry and Health Sciences, The University of Melbourne, Parkville, VIC, Australia. 3Melbourne Dementia Research Centre, The Florey Institute of Neuroscience and Mental Health and The University of Melbourne, Parkville, VIC, Australia. 4Department of Molecular Medicine, The Scripps Research Institute, La Jolla, CA, USA. Email: [email protected]; [email protected]

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Sleep quality declines with aging. In mice, wake-promoting hypocretin neurons, normally silent during sleep, become hyperexcitable with age, resulting in intrusions of wakefulness into sleep. This discovery may lead to new therapies to improve sleep in aging and related disorders.

wakefulness and become inactive with sleep. Narcolepsy type 1 (NT1) is caused by the loss of hypocretinergic neurons and is characterized by unstable sleep, wakefulness, and cataplexy (loss of muscle tone) (7). Accordingly, hypocretin receptor antagonists, which block hypocretin-induced wakefulness, produce a more natural sleep architecture than classic hypnotics: benzodiazepines or “z-drugs” (e.g., zolpidem), which activate inhibitory g-aminobutyric acid type A (GABAA) receptors, and sedative antidepressants and antipsychotics, which act by globally dampening brain activity (8). Three dual orexin receptor antagonists (DORAs) are now approved for treating insomnia: suvorexant, lemborexant, and daridorexant. Li et al. report age-dependent decreased hypocretin neuron density, which could be expected to destabilize sleep-wakefulness, as seen in NT1. Others have also observed decreased hypocretin neuron density with aging in various species, including humans (9). However, the detailed analyses of remaining hypocretin neurons by Li et al. provide a deeper level of understanding of the underlying mechanisms leading to disrupted sleep. Using fiber photometry and calcium imaging, Li et al. showed calcium peaks in hypocretin neurons associated with wakefulness. During the inactive (sleep dominant) phase, these calcium transients were more frequent and lower in amplitude in old versus young mice and were associated with increased wakefulness. This suggested a lower threshold to arousal in aged hypocretin neurons and increased hypocretin release. Indeed, this was confirmed by the increased wakefulness induced by optogenetic stimulation of hypocretin neurons and their electrophysiological hyperexcitability in aged mice. Investigating possible causes of this intrinsic hyperexcitability, Li et al. discovered a reduced expression of subunit 2 of the

KCNQ voltage-gated potassium channel. Channels composed of KCNQ subunits 2 and 3 are responsible for M-currents, which maintain the cell membrane potential below the threshold for action potentials, inhibiting neuronal activity. Li et al. found reduced M-currents in aged hypocretin neurons, explaining their hyperactivity. By selectively reducing KCNQ2/3 expression in hypocretin neurons using CRISPR-Cas9 in young mice, the authors mimicked aspects of hypocretin neuron hyperexcitability and non–rapid eye movement (NREM) sleep instability of old mice. Characterized by slower electroencephalographic (EEG) frequencies, NREM sleep is associated with learning and memory consolidation and is the most disrupted sleep state with age (2). The KCNQ channel blocker XE991 stimulated wakefulness in young mice, whereas in old mice, the KCNQ2/3 channel opener flupirtine improved NREM sleep quantity and stability and, notably, enhanced recognition memory. Increased NREM sleep stability was also induced by treating aged mice with the DORA MK6096. Sleep is also disrupted in several neurodegenerative and neuropsychiatric diseases, including anxiety, depression, autism, posttraumatic stress disorder, and Parkinson’s and Alzheimer’s diseases. Li et al. show that despite commonalities such as hypocretin neuron loss and sleep-wakefulness fractionation in aging and NT1 (but not cataplexy), the disrupted sleep of older mice was mechanistically different from that of a mouse model of NT1 (although resting membrane potential of surviving hypocretin neurons was increased in both aging and early stages of hypocretin neuron loss in the NT1 mouse model, indicating some form of circuit-based compensation in both). Given the severe hypocretin neuron loss in advanced NT1, KCNQ2/3 channel openers or hypocretin receptor antagonists should not consolidate sleep in NT1 patients. science.org SCIENCE

PHOTO: ENES EVREN/ISTOCKPHOTO.COM

Hypocretin neuron hyperexcitability underlies disrupted sleep quality associated with age

Indeed, DORAs are contraindicated in NT1 owing to an increased risk of cataplexy (8). However, this leads to questions about the mechanisms underlying disrupted sleep in other pathologies. Like aging, Alzheimer’s disease is commonly accompanied by disrupted sleep, as well as hypocretin neuron loss (10) and increased hypocretinergic tone (11, 12). It will thus be important to determine whether aging and Alzheimer’s disease share KCNQ2/3 channel-induced hypocretin neuron hyperactivity as a common mechanism. NREM sleep is important for the clearance of toxic, misfolded brain peptides and proteins (13) such as b-amyloid (Alzheimer’s disease), tau (tauopathies), and a-synuclein [Parkinson’s disease (14)]. Because these products can also directly disrupt sleep, hypnotic-enhanced NREM sleep may further enhance sleep quality and delay disease progression by reducing their accumulation (14, 15). However, classical hypnotics are unlikely to unlock such benefits. These broad-spectrum inhibitors of neuronal activity can induce cognitive complaints and falls and are thus contraindicated in such disorders and in older people in general. DORAs, by contrast, have a better sideeffect profile in these domains (8). Together with Li et al.’s evidence of improved recognition memory with flupirtine in aged mice, selective targeting of hypocretinergic mechanisms may prove superior in reaping the rewards of pharmacologically enhanced sleep in older people in both health and disease. The discovery by Li et al. reveals an agedependent mechanism underlying sleep disruption and thus reopens the search for new, targeted strategies to combat sleep disturbances in older people, and future research has the potential to expand to neurodegenerative disorders. If translated clinically, these findings pave the way for the development of sleep medications that specifically dampen hypocretin neuron hyperactivity to improve sleep and mental and physical health in older people. j

GRAPHIC: K. FRANKLIN/SCIENCE

REFERE NCES AND NOTES

1. 2. 3. 4. 5. 6. 7. 8. 9. 10. 11. 12. 13. 14.

D. Kocevska et al., Nat. Hum. Behav. 5, 113 (2021). B. A. Mander, J. R. Winer, M. P. Walker, Neuron 94, 19 (2017). C. J. Lowe et al., Neurosci. Biobehav. Rev. 80, 586 (2017). D. J. Foley et al., Sleep 18, 425 (1995). S.-B. Li et al., Science 375, eabh3021 (2022). T. E. Scammell et al., Neuron 93, 747 (2017). C. L. A. Bassetti et al., Nat. Rev. Neurol. 15, 519 (2019). D. Hoyer et al., Br. J. Clin. Pharmacol. 86, 244 (2020). N. J. Hunt et al. Neurobiol. Aging 36, 292 (2015). J. Oh et al., Alzheimers Dement. 15, 1253 (2019). Y. A. Dauvilliers et al., Front. Aging Neurosci. 6, 119 (2014). C. Liguori et al., JAMA Neurol. 71, 1498 (2014). M. Nedergaard, S. A. Goldman, Science 370, 50 (2020). M. M. Morawska et al., Sci. Transl. Med. 13, eabe7099 (2021). 15. B. P. Lucey, Neurobiol. Dis. 144, 105031 (2020).

GENETICS

Inferring human evolutionary history Unified genetic genealogy improves our understanding of how humans evolved By Jasmin Rees1,2 and Aida Andrés1,2

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enomes are invaluable tools for inferring the demographic and adaptive history of human populations, including migrations, population splits, admixture, and genetic adaptations. Growing datasets of modern and ancient genomes make this possible, but their massive size comes with important challenges, demanding techniques that analyze immense amounts of data in reasonable amounts of time while using as much information as possible. Combining genomes from different datasets poses perhaps an even greater challenge, especially when it comes to integrating ancient and modern genomes. On page 836 of this issue, Wohns et al. (1) report surmounting some of these challenges to construct the largest human genealogy to date, integrating modern and ancient genomes from multiple datasets to infer key events in human history together with their timings and geographical locations. Phylogenetic trees are used to represent the evolutionary or genetic relationships

among species. Similar trees can represent the relationships among individuals within a species, analogous to how family genealogies represent relationships between family members. However, because of the effects of recombination, each locus has a slightly different evolutionary history and therefore a different tree. Tree-recording methods (2) can infer these trees along the genome, with each tree representing what can be considered a nearly complete history of the locus. Consequently, tree recording is superior to most classical methods, which condense complicated evolutionary patterns in relatively simple summary statistics. By combining trees across the genome, a theoretical genealogy can be generated that embodies the genetic relationships among sampled individuals and their inferred ancestors, within and across populations. If the sampling of genomes was sufficiently comprehensive, such genealogy would in theory represent relationships over the entire species, capturing the genetic history of modern humans today. Owing to a series of impressive theoretical and computational advances, genetic

Human genealogy reconstruction and geographical inference By building the tree from modern human and high-quality ancient genomes, one can infer ancestral human relationships. Using additional ancient human samples to help infer the ages of alleles, Wohns et al. built a unified genealogy that also includes the geographical location of inferred ancestors, which gives information about populations and their migrations through human history. Modern human samples

Inferred ancestors Ancient humans

Modern humans Archaic humans

Adding ancient DNA

ACKNOWLEDGMENTS

L.H.J. has consulted for Eisai Co., Ltd. 10.1126/science.abo1822 SCIENCE science.org

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trees can now be inferred for thousands of genomes (3–7). Analyses of these trees have already improved our knowledge of human demography (4, 5, 8, 9) and promise to improve our ability to identify targets of natural selection (5, 8, 10–12). Further, high-quality ancient genomes can be directly integrated in the tree, which greatly increases the certainty of evolutionary processes by supporting inferences with data from the past. This is particularly helpful to study populations that are extinct or that contributed little to modern populations, such as Neanderthals and Denisovans (archaic humans) (13, 14), and tree-based studies are helping to create a better understanding of the nature of interbreeding between modern and archaic groups (5, 8, 9). Unfortunately, the DNA in ancient remains is usually highly degraded and most ancient genomes are not of sufficient quality to be fully incorporated into the trees. Wohns et al. present an approach that aims to skirt inaccuracies introduced by ancient DNA by using such ancient genomes only to help time the emergence of alleles (see the figure). This allows the use of hundreds of ancient genomes while limiting the effects of errors. They generated an impressive, unified human genealogy from >3500 modern and high-quality ancient genomes from >215 different human populations, using >3000 additional ancient genomes to improve inferences from the trees. With this unified genealogy, key events in history, such as population size changes, splits, or migrations, become clearly apparent. They identify well-resolved events, such as the out-of-Africa migration, and suggest multiple severe reductions in population size through human history. Further, Wohns et al. propose a new method that, applied to the unified genealogy, allows them to estimate ancestral geographical locations of evolutionary events. Although there have been other efforts to place past events geographically (15), Wohns et al. use a nonparametric method to estimate the theoretical location of inferred human ancestors simply as the midpoint of the geographic coordinates of their descendants—with these calculations extended backward up the tree to reach a theoretical common ancestor of all individuals. Using this method, Wohns et al. infer an average ancestral location of all sampled humans in Northeast Africa by 72,000 years ago and until the oldest 1

UCL Genetics Institute, Department of Genetics, Evolution and Environnment, University College London, London, UK. 2Genetics and Genomic Medicine Programme, Great Ormond Street Institute of Child Health, University College London, London, UK. Email: [email protected]

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common ancestors of all individuals. This simple method works well to refine known ancestral locations and, as sampling improves, it has the potential to identify currently unknown human movements. More generally, the trees generated in this study will undoubtedly prove useful to those studying human evolution. Although tree-recording methods represent an exciting and promising avenue of harmonizing datasets across time and space, as demonstrated by Wohns et al., they are not without their limitations. There remains uncertainty in evolutionary parameters and ancient genomes, and it is unlikely that the use of low-quality ancient DNA will ever be without a degree of error, except when using rare high-quality genomes or if inferring missing data becomes substantially more accurate. Still, as genomic datasets continue to grow, genealogical methods will be increasingly useful to represent the wealth of genomic data. Perhaps most importantly, as larger numbers of modern and ancient genomes from underrepresented populations become available, our understanding of human demography, currently still biased to well-sampled populations, will improve in both detail and scope. The power and resolution of tree-recording methods promise to help clarify the evolutionary history of humans and other species. It is likely that the most powerful ways to infer evolutionary history going forward will have their foundations firmly set in these methods. j REF ERENCES AND NOTES

1. A. W. Wohns et al., Science 375, eabi8264 (2022). 2. M. D. Rasmussen, M. J. Hubisz, I. Gronau, A. Siepel, PLOS Genet. 10, e1004342 (2014). 3. J. Kelleher, A. M. Etheridge, G. McVean, PLOS Comput. Biol. 12, e1004842 (2016). 4. J. Kelleher et al., Nat. Genet. 51, 1330 (2019). 5. L. Speidel, M. Forest, S. Shi, S. R. Myers, Nat. Genet. 51, 1321 (2019). 6. K. Harris, Nat. Genet. 51, 1306 (2019). 7. P. Ralph, K. Thornton, J. Kelleher, Genetics 215, 779 (2020). 8. L. Speidel et al., Mol. Biol. Evol. 38, 3497 (2021). 9. N. K. Schaefer, B. Shapiro, R. E. Green, Sci. Adv. 7, abc0776 (2021). 10. Y. Field et al., Science 354, 760 (2016). 11. A. J. Stern, P. R. Wilton, R. Nielsen, PLOS Genet. 15, e1008384 (2019). 12. A. J. Stern, L. Speidel, N. A. Zaitlen, R. Nielsen, Am. J. Hum. Genet. 108, 219 (2021). 13. M. Meyer et al., Science 338, 222 (2012). 14. K. Prüfer et al., Nature 505, 43 (2014). 15. M. M. Osmond, G. Coop, bioRxiv 10.1101/2021.07.13.452277 (2021). ACKNOWL EDGMENTS

J.R. is funded by the National Institute for Health Research Great Ormond Street Hospital Biomedical Research Centre. A.A. is funded by University College London’s Wellcome Institutional Strategic Support Fund 3 (204841/Z/16/Z). 10.1126/science.abo0498

MEDICINE

Anticipating antibiotic resistance Machine learning can use clinical history to lower the risk of infection recurrence By Jean-Baptiste Lugagne1,2 and Mary J. Dunlop1,2

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hen a patient is diagnosed with a bacterial infection, clinicians perform antibiotic susceptibility tests in the laboratory and use the results to prescribe an appropriate antibiotic. But recurrence rates are high; for example, ~25% of women with urinary tract infections (UTIs) develop another infection within 6 months (1, 2). On page 889 of this issue, Stracy et al. (3) reveal that recurrent infections are often driven by a different strain than the original infection. Although correctly prescribing a susceptibility-matched antibiotic reduces recurrence rates overall, it also increases the chances of developing a resistant infection caused by a different strain. Thus, treatment is a double-edged sword, in which susceptibility-matched treatments can pave the way for resistant strains lurking in the microbiota. The authors find that this risk can be minimized with a data-driven approach that incorporates population-wide statistics and the patient’s personal history through a machine learning model to make antibiotic recommendations. Key to this study is a large longitudinal dataset containing information about UTIs and wound infections, including antibiotic susceptibility profiles and prescribed antibiotics, for male and female patients of all ages in Israel’s Maccabi Healthcare Services between 2007 and 2019. In most cases, antibiotic treatment of the initial infection is effective. However, in 10% of UTIs and 6% of wound infections, patients experience early recurrence, returning with another infection within 28 days of the original. Some of these early recurrences are the result of erroneous prescription of an antibiotic that the infection was resistant to, as can hap1

Department of Biomedical Engineering, Boston University, Boston, MA, USA. 2Biological Design Center, Boston University, Boston, MA, USA. Email: [email protected] science.org SCIENCE

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SCIENCE science.org

Predicting resistance according to treatment history A machine learning model built with data from thousands of patients with wound infections and urinary tract infections identified the factors that contribute to antibiotic resistance in recurrent infections. A patient’s history of infections and antibiotic treatments can then be used with their demographic data to predict which candidate antibiotics would likely prevent a recurrent infection. Susceptible

Antibiotic susceptibilities

pen when drugs are prescribed to provide rapid clinical intervention while awaiting results from susceptibility tests (4). However, a substantial fraction of cases fall into the insidious category of being appropriately treated with susceptibility-matched antibiotics and yet returning with an antibiotic-resistant infection. How do these resistant strains emerge? Stracy et al. carried out genomic sequencing of the bacteria, providing a detailed view of the strains and species of the original infection compared with the ones that caused it to recur. This analysis reveals an underappreciated path to reinfection, with the original species being treated and eliminated but with the treatment ultimately setting the stage for other resistant strains to emerge. Recent studies provide compelling examples of how a patient’s microbiota serves as a reservoir, such as uropathogenic strains being harbored in the gut (2, 5). This analysis also joins a growing list of studies that highlight the power and potential of integrating genome sequencing data with clinical records (6, 7). Building on the extensive dataset of infection and treatment histories, Stracy et al. develop a machine learning algorithm for patient-specific recommendations (see the figure). This strategy is successful because the patient’s risk of developing a recurrent infection is strongly linked to their treatment and infection history. The authors use multivariate logistic regression, a powerful long-established tool for medical outcome predictions (8), to assess the risk of early recurrence for each antibiotic candidate. The algorithm then identifies the antibiotic that is least likely to cause an infection to recur early and be resistant to the prescribed antibiotic. Notably, the model uses only 13 parameters to fit the data for each UTI antibiotic, and eight in the case of wound infections, in which the parameters weight factors such as age, sex, pregnancy status, catheter use, and infection history. These recommendation algorithms are evaluated against statistical models of early recurrence and are predicted to reduce the rate of early resistance recurrences of UTIs and wound infections by almost half compared with those of physicians’ susceptibility-matched prescriptions. This is one of the great advantages of machine learning approaches: By systematically reviewing all available patient information, with a statistical model built on thousands of training samples, the algorithm can identify subtle patterns and provide valuable insights and recommendations to support physicians in their decisions (4, 9). The algorithms are also predicted to significantly improve on current physician practices

Resistant R Re e

Prescribed antibiotic

A B C D E ...

Past infections

Current infection

Age, sex, catheter use, pregnancy status

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Antibiotic recommendation for current infection Probability of resistance 0 1 A B C D E ...

sess whether resistant infections that extend beyond the 28-day window are also prevented. It is also unknown how large and diverse the training sets need to be and, once trained, how robust the recommendation system is, for example, to missing data points or clerical errors. More generally, data-driven approaches to health care decisions face numerous social, legal, and ethical challenges, as highlighted recently by the World Health Organization (WHO) (12). Algorithms can entrench suboptimal or even discriminatory practices (13). Although the recommendation model presented by Stracy et al. is not fitted directly to the clinicians’ decisions if, for example, the responses of 10- to 19-year old women to fosfomycin are underrepresented in the training set, predictions under these conditions will be less reliable. It is also unclear how the model will adapt to shifts in medical practices— for example, in the case of newly available antibiotics. Still, machine learning recommendation systems such as the one presented by Stracy et al. have the potential to substantially improve patient outcomes and could play a major role in mitigating antibiotic resistance. The current wave of data-driven methods for health care presents an opportunity not only to tackle broad public health issues but to harness their power to introduce new data collection standards, evaluation metrics, and training paradigms (14, 15). Essential to the success of these methods is the availability of both longitudinal datasets and interdisciplinary studies, such as those based on genomic sequence analysis, that provide fundamental insights into the mechanisms by which resistance emerges. j REF ERENCES AND NOTES

even when they are constrained to recommend different types of antibiotics at frequencies that match present-day practices. This is essential because other factors, such as side effects and ease of use, inform decisions about antibiotic selection. The risk assessment for each antibiotic and a quantified contribution profile for each patient risk factor, such as age or resistance history, can be retrieved. The decision is therefore interpretable, a critical step toward establishing trust in machine learning recommendation systems for health care (10, 11). However, these algorithms are not ready to prescribe antibiotics just yet. The algorithms were not evaluated on actual patients but against statistical estimates of the chances of early resistance recurrences. Further studies are required to as-

1. A. L. Flores-Mireles, J. N. Walker, M. Caparon, S. J. Hultgren, Nat. Rev. Microbiol. 13, 269 (2015). 2. B. M. Forde et al., Nat. Commun. 10, 3643 (2019). 3. M. Stracy et al., Science 375, 889 (2022). 4. I. Yelin et al., Nat. Med. 25, 1143 (2019). 5. K. L. Nielsen, P. Dynesen, P. Larsen, N. Frimodt-Møller, J. Med. Microbiol. 63, 582 (2014). 6. X. Didelot, R. Bowden, D. J. Wilson, T. E. A. Peto, D. W. Crook, Nat. Rev. Genet. 13, 601 (2012). 7. M. Magruder et al., Nat. Commun. 10, 5521 (2019). 8. P. W. F. Wilson et al., Circulation 97, 1837 (1998). 9. A. Rajkomar, J. Dean, I. Kohane, N. Engl. J. Med. 380, 1347 (2019). 10. C. M. Cutillo et al., NPJ Digit. Med. 3, 47 (2020). 11. A. F. Markus, J. A. Kors, P. R. Rijnbeek, J. Biomed. Inform. 113, 103655 (2021). 12. WHO, Ethics and governance of artificial intelligence for health: WHO guidance (WHO, 2021); www.who.int/ publications/i/item/9789240029200. 13. Z. Obermeyer, B. Powers, C. Vogeli, S. Mullainathan, Science 366, 447 (2019). 14. J. F. Rajotte et al., GoodIT 2021 Proc. 2021 Conf. Inf. Technol. Soc. Good, 10.1145/3462203.3475875 (2021). 15. S. Hooker, Patterns 2, 100241 (2021). 10.1126/science.abn9969 25 FEBRUARY 2022 • VOL 375 ISSUE 6583

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ORGANIC CHEMISTRY

Dimerization decrypts antibiotic activity Direct dimerization simplifies the synthesis of himastatin and elucidates its mode of action

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oxygen atoms, as well as forge the necessary carbon–carbon bond selectively at one specific position on each monomer. Prior approaches to natural products related to 1 had unsuccessfully attempted similar late-stage dimerizations, and lengthy two-directional strategies were used in which a simplified dimeric core is grown outward into each macrocyclic half. This approach was initially showcased in Kamenecka and Danishefsky’s inaugural synthesis of 1 (6) and in later ef-

C5 prefunctionalization. Mechanistic studies showed that such couplings likely proceed through dimerization of an aniline radical cation, forming the new C–C bond at the most accessible C5 position. To prepare the necessary monomer 2, they combined the convenience of solid-phase synthesis of a pentadepsipeptide with solution-phase coupling of the more tricky cyclotryptophan unit and a final macrolactamization to form the 18-membered ring in a highly efficient

ith the emergence of drug-resistant bacteria that can evade current frontline therapeutics, the need for antibiotics with new modes of action is increasingly urgent (1). One emerging strategy to address this need is to revisit previously identified antibiotics of promise and apply modern medicinal chemistry and biochemical tools to improve their activity and unveil their often ill-defined modes of action (2, Streamlining dimerization 3). Among such natural products Chemical routes to forming large peptide dimers like himastatin (1) from its monomer (2) usually are unsuccessful. is himastatin (1), a dimeric pepD’Angelo et al. report a bioinspired oxidative coupling route that performs this step in useful yields. tide antibiotic isolated in 1990 that shows good activity against Coupling reactions Me Me Cyclization Me Me Me Gram-positive bacteria, albeit Me O Me O FmocHN through a largely unknown mode HN Me HO H 5 Teoc Hybrid solid- and O N O TESO of action (4). On page 894 of this N O O N O N CO2Allyl solution-phase synthesis issue, D’Angelo et al. (5) develop N O O N O NH OH OTBS an efficient chemical synthesis HO2C (25% overall) H H N NH Me H H N of himastatin through a bioinHO2C H O O NHFmoc Solid Me OH spired dimerization of its native support Me Me Me monomeric units. This approach NHFmoc Himastatin monomer: 2 provides a blueprint to access not Me Ot-Bu only this complex target and its Cu(SbF6)2 DTBMP derivatives, but also molecular Me Direct dimerization (oxidation) probes that allow for its mode of of unprotected monomers Me OH H action to be elucidated (5). N Me HN The most intuitive simplificaMe Me H H HO O + H H N Me tion in the retrosynthesis of a N O O N N O challenging dimeric target such Me N O O HN N O HO H H as 1 would be to break its strucOH O N OH 5 NH O Me O N O ture into two units of its monoN O O 5' HO (40%) Me N O OH mer, depsipeptide 2, by cleaving Me Me H H Me NH the central C5–C59 bond. This apN N H Himastatin: 1 proach reduces the synthetic task OH Me +N H H Dye-tag to the preparation of monomer site Radical-radical coupling Me 2, provided a method could be found to unite the halves at the Abbreviations: Me, methyl; t-Bu, tert-butyl; Teoc, 2-(trimethylsilyl)ethoxycarbonyl; Fmoc, 9-fluorenylmethoxycarbonyl; TBS, tert-butyl(dimethyl)silyl; TES, triethylsilyl; and DTBMP, 2,6-di-tert-butyl-4-methylpyridine. correct position. Such a dimerization is used by the producing organism in the biosynthesis of 1 through forts for the synthesis of chloptosin (7, 8). manner (see the figure). With monomer 2 in P450-catalyzed oxidative dimerization of 2. From a biological standpoint, the dimeric hand, the authors performed the dimerizaBeing able to effect such a transformation structure of 1 is vital for its antibacterial tion with a stoichiometric copper(II) oxidant by chemical means is a daunting challenge. properties, with monomeric compounds like to deliver 1 in 40% yield. Any developed method would need to toler2 showing no activity (6). Given the complexity of the substrate, ate the numerous functional groups in the Inspired by the simplicity of the biosynthe obtained yield is surprisingly high, and complex peptide backbone of 2, which might thetic route, D’Angelo et al. began by dethe efficiency of the dimerization is notable interfere through their reactive nitrogen and veloping a dimerization process on simpler given the absence of any protecting groups cyclotryptophan and cyclotryptamine comin 2 that would typically be used to mask pounds using either a silver(I)- or copper(II)reactive groups that might otherwise risk Department of Biochemistry, University of Texas based oxidant to selectively arrive at C5–C59 being oxidized themselves or sequester the Southwestern Medical Center, Dallas, TX 75390, USA. Email: [email protected] dimers in useful yields without the need for metal oxidant. The convergent synthesis of 2 820

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science.org SCIENCE

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By Myles Smith

made it straightforward and robust enough for the authors to prepare structural analogs of 2, and in turn 1, to probe their activity. Assaying these compounds for antibacterial activity revealed interesting trends. For example, the sense of chirality of 1 had little effect, with its enantiomer ent-1 and mesodiastereomer displaying a potency similar to that of natural 1. The dependence on overall topology rather than absolute chirality points to a physical interaction underlying their activity. Although it had been suggested that 1 may target bacterial membranes, no definitive evidence has been available (9). D’Angelo et al. prepared a himastatin probe in which one isopropyl group is replaced with a fluorescent dye. Antibacterial activity was only maintained when one half of the molecule bore this bulky tag. Prior two-directional approaches would have great difficulty accessing this heterodimer. Confocal microscopy experiments in Bacillus subtilis revealed that himastatin induces membrane defects that ultimately permeabilize the cell. This mode of action is reminiscent of that of daptomycin, a structurally unrelated cyclic peptide antibiotic (10). The concise synthetic route of D’Angelo et al. should enable in-depth investigations of structural change to himastatin that could tune the potency and selectivity. Additionally, experiments that explore the molecular basis of the interaction with the bacterial membrane, as has recently begun to become apparent for daptomycin (11), could provide opportunities for both fundamental biophysical discoveries and inform designs of other molecules for membrane perturbation. From a synthetic standpoint, the bold dimerization showcased may inspire similarly direct approaches to complex dimeric or oligomeric natural products by coupling native monomers. j

ASTRONOMY

A crooked spinning black hole New observations challenge the current understanding of black hole formation By Ferdinando Patat1 and Michela Mapelli2

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o different extents, all celestial bodies rotate, planets and stars alike. Things get particularly interesting when the objects are part of gravitationally bound configurations such as a binary system, in which the two bodies revolve around each other. In the absence of external perturbations, their rotation axes tend to be aligned with each other and perpendicular to the orbital plane. This trend is usually true even for exotic systems, such as x-ray binaries, in which a star revolves around a black hole. On page 874 of this issue, Poutanen et al. (1) present the case of x-ray binary system MAXI J1820+070, which counterintuitively has the spin axis of the black hole strongly misaligned to the orbital plane. This deeply challenges the current understanding of how black holes can be formed and indicates the presence of a powerful kick produced by the supernova that generated the black hole. Our star, the Sun, has no companions. Although one may view this arrangement as the norm, a large fraction of stellar objects in a galaxy actually belong to binary or even

triple systems. Multistar systems are more likely for heavier stars, with about 80% of stars with masses 15 times larger than that of the Sun (Msun) being in a multiple system (2). Stars with masses >20Msun are extremely short-lived, with a typical life span shorter than 10 million years. During their brief existence, massive stars in tight binary systems interact with the companion in several ways. For example, one of the two stars may transfer part of its matter to the other, changing the mass ratio and other orbital properties of the system. Tides can arise when the gravity force exerted by one star onto the other varies substantially from one point of the stars’ surface to another, resulting in a tidal pull. Tides tend to align their rotation axes perpendicularly to the orbital plane of the system. The death of a massive star, often accompanied by a formidable supernova explosion, is expected to leave behind a very compact and massive stellar object, such as a black hole. Because of the powerful asymmetric mass ejection, the newborn black hole receives what is known as a “natal kick.” This kick might tilt the black hole’s rotation axis, misaligning it with respect to the axis of the

A tilted black hole spinning in a binary system Astronomers have observed a black hole that spins along an axis strongly misaligned with the orbital plane of the binary system MAXI J1820+070. This challenges current models on the formation of black holes generated by supernovae.

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REFERENCES AND NOTES

1. H. W. Boucher et al., Clin. Infect. Dis. 48, 1 (2009). 2. G. D. Wright, Can. J. Microbiol. 60, 147 (2014). 3. P. M. Wright, I. B. Seiple, A. G. Myers, Angew. Chem. Int. Ed. 53, 8840 (2014). 4. K. S. Lam et al., J. Antibiot. (Tokyo) 43, 956 (1990). 5. K. A. D’Angelo, C. K. Schissel, B. L. Pentelute, M. Movassaghi, Science 375, 894 (2022). 6. T. M. Kamenecka, S. J. Danishefsky, Chemistry 7, 41 (2001). 7. S.-M. Yu, W.-X. Hong, Y. Wu, C.-L. Zhong, Z.-J. Yao, Org. Lett. 12, 1124 (2010). 8. A. J. Oelke et al., Chemistry 17, 4183 (2011). 9. S. W. Mamber et al., Antimicrob. Agents Chemother. 38, 2633 (1994). 10. A. Pokorny, P. F. Almeida, J. Membr. Biol. 254, 97 (2021). 11. R. Moreira, S. D. Taylor, Angew. Chem. Int. Ed. 61, e202114858 (2022).

Black hole spin axis

Orbital plane axis

Companion star Black hole Accretion disk

ACKNOWLEDGMENTS

The Welch Foundation (I-2045) and University of Texas Southwestern Medical Center (W. W. Caruth Jr. Scholarship) are acknowledged for funding. 10.1126/science.abn8327 SCIENCE science.org

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orbital plane. Under the most extreme circumstances, this kick can even unbind the binary system. In cases in which the binary system survives the supernova explosion and remains gravitationally bound, mass transfer from the smaller star to the black hole might ensue. This stripped-away mass from the star would take form in the shape of an accretion disk, which lies in the orbital plane around the black hole. Only part of this material would disappear below the event horizon—the point of no return—and falls into the black hole. The rest of the material is ejected at relativistic speeds in two symmetric, collimated jets, following the strong magnetic field along the spin axis of the black hole (3, 4). This mechanism is unstable and undergoes erratic and powerful outbursts, producing radio and x-ray emissions that can be and have been observed (see the figure). When the black hole was formed by the exploding massive star, as it collapsed inward its angular momentum was likely conserved. Therefore, as in the case of a ballet dancer bringing her arms closer to her body to increase the rotation velocity, the resulting spinning speed of the collapsing star is greatly increased and can reach more than a thousand rotations per second. This has important relativistic consequences, such as the modification of space-time around the eventual black hole. In the absence of external perturbations—for example, the gravitational pull from other stars in a multistar system or within a stellar cluster—mass transfer and tidal forces tend to align the rotation axes and keep the spin axis of everyone perpendicular to the orbital plane. This geometry is assumed, for example, when calculating the mass of the black hole. However, the aforementioned alignment hypothesis is all but easy to verify in observational astronomy. Poutanen et al. have devised an ingenious technique that makes use of linear polarimetry and applied it to the x-ray binary system known as MAXI J1820+070. This system was discovered during an outburst by the All-Sky Automated Survey for Supernovae (ASAS-SN), and x-ray measurements were performed by the MAXI imager on board the International Space Station in July 2018 (5). At about 10,000 light-years from Earth, the system hosts a black hole with ~8 Msun, which orbits around a star with ~0.5 Msun. The axial offset between the black hole and the orbiting star in MAXI J1820+070 1

European Southern Observatory, D-85748 Garching, Germany. 2Physics and Astronomy Department “G. Galilei,” University of Padova, 35122 Padova, Italy. Email: [email protected]

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is more than 40°—the largest offset ever reported. This has crucial implications for theories of black hole formation (6). A substantial natal kick might either split the binary system or tilt the orbital plane with respect to its initial orientation (7). Because mass accretion (8) and tides (9) tend to align the spin axis to the orbital angular momentum of the binary system, the natal kick from the supernova is the main if not the only mechanism that can produce such a misalignment (10). Although this explanation is very plausible, it is still a matter of debate (11). Alternatively, there are cases in which mass accretion does not necessarily result in spin alignment (12). Hence, measuring a substantial axial offset is to be considered as the smoking gun of either a large natal kick or a dynamical formation scenario for the binary system (13). Furthermore, finding a large axial offset in this system is particularly surprising because the evolution after the supernova explosion can only reduce the misalignment induced by the kick (8). This implies that it must have been even larger when the black hole was born. When compared with the theoretical predictions, the reported lower limit of the misalignment angle is very high; this may call for the need of revising the existing models for these systems. Given the low mass of the companion star (6), MAXI J1820+070 will not evolve into a binary black hole. Nevertheless, the spin-orbit misalignment in MAXI J1820+070 is a crucial step forward for interpreting the observed distribution of spin tilts in Laser Interferometer Gravitational-wave Observatory (LIGO)–Virgo event candidates (14, 15). j REF ERENCES AND NOTES

1. J. Poutanen et al., Science 375, 874 (2022). 2. G. Duchêne, A. Kraus, Annu. Rev. Astron. Astrophys. 51, 269 (2013). 3. J. C. McKinney, A. Tchekhovskoy, R. D. Blandford, Science 339, 49 (2013). 4. P. Polko, J. C. McKinney, Mon. Not. R. Astron. Soc. 464, 2660 (2017). 5. M. Espinasse et al., Astrophys. J. Lett. 895, L31 (2020). 6. M. A. P. Torres et al., Astrophys. J. Lett. 882, L21 (2019). 7. M. Mapelli, Handbook of Gravitational Wave Astronomy (Springer, 2021). 8. T. J. Maccarone, Mon. Not. R. Astron. Soc. 336, 1371 (2002). 9. J. Hurley, C. A. Tout, O. Pols, Mon. Not. R. Astron. Soc. 329, 897 (2002). 10. D. Gerosa et al., Phys. Rev. D 98, 084036 (2018). 11. P. Atri et al., Mon. Not. R. Astron. Soc. 489, 3116 (2019). 12. J. Stegmann, F. Antonini, Phys. Rev. D 103, 063007 (2021). 13. C. L. Rodriguez, M. Zevin, C. Pankow, V. Kalogera, F. A. Rasio, Astrophys. J. Lett. 832, L2 (2016). 14. D. Wysocki et al., Phys. Rev. D 97, 043014 (2018). 15. R. Abbott et al., arXiv:2111.03606 [gr-qc] (2021). ACKNOWL EDGMENTS

The authors thank S. Piranomonte for her help during the preparation of this article. M.M. acknowledges support from the European Research Council Consolidator grant DEMOBLACK, under contract 77001. 10.1126/science.abn5290

PHOTONICS

Flashing light with nanophotonics Manipulation and enhancement of scintillation is achieved in nanophotonic structures By Renwen Yu and Shanhui Fan

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hen a material is bombarded with high-energy particles, such as free electrons or x-ray photons, it may emit light in the visible frequency. This process, known as scintillation, is important for applications such as medical imaging and nondestructive inspection (1). For these applications, enhancing and controlling the light emission is of critical importance to improve their capabilities involving precision and resolution. Toward this goal, researchers are constantly looking for better scintillator materials (2) and better ways to control the scintillation processes. One way to improve the functionalities of scintillator materials is by introducing photonic structures to enhance scintillation (3). On page 837 of this issue, Roques-Carmes et al. (4) report a method to optimize scintillation using nanophotonic structures that can achieve orders-ofmagnitude enhancement. The scintillation process that occurs inside a solid material can be broken down into three smaller steps. In the first step of the process, the incoming high-energy particles create a nonequilibrium distribution of electrons inside the material. In the second step, the now-excited electrons diffuse through the material to create a steadystate density distribution of secondary electrons. In the final step, these secondary electrons radiatively decay at certain sites in the material, shedding their excess energy as light. There is extensive research on how to manipulate electromagnetic fields using nanophotonic structures, such as nanostructures with periodically varying refractive indices, for controlling and enhancing these light emissions (5). Consequently, by integrating the scintillator with or patterning it into a nanophotonic structure, it should be posscience.org SCIENCE

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sible to enhance the scintillation Improving scintillator capabilities with cutouts tillation spectrum in a patterned yield and control the emitted light cerium-doped yttrium aluminum By stacking patterned cutouts of silicon on a silica layer and creating spectrum. However, to design garnet scintillator under x-ray patterned dimples on cerium-doped yttrium aluminum garnet, researchers nanophotonics-enhanced scintilcompared with an unpatterned improved the efficiency of, and offered wavelength-dependent tunability to, lation requires a comprehensive sample. The higher efficiency is the two scintillation devices. understanding of the complex beneficial for scintillation appliElectrons Light process involving both electron cations where x-ray exposure is of and photon dynamics. concern. Moreover, by using the Roques-Carmes et al. provide inverse-design technique (11) toa complete model for the entire gether with electromagnetic reciscintillation process involving procity, further enhancements Patterned silicon the use of nanophotonic strucbeyond what has been demontures. They modeled the process strated in the experiments may of electron excitation as a result be achievable. For both experiSilica (scintillating) of the incoming high-energy parments, their results show good ticles, as well as the subsequent agreement with the back-to-back Silicon substrate excitation and spatial transportatheoretical modeling that incortion of secondary electrons (6). porates both electronic and phoThe model can produce the dentonic processes. sity distribution of the nonequiThe demonstrated nanophoX-ray Light librium secondary electrons that tonic scintillators show that one is responsible for the ultimate can engineer and enhance the perscintillation. To model the radiaformance of a given scintillating tive decay of these electrons at material through nanostructures. specific crystal defect sites where The work of Roques-Carmes et Cerium-doped yttrium scintillation occurs, the model al. points to new possibilities for aluminum garnet also computes the electronic levapplications ranging from highels of these defect sites and modresolution x-ray detectors used els the radiative transition (7) bein medical imaging to efficient tween these electronic levels. ultraviolet-light sources. The deFrom these electronic simulaveloped comprehensive theoretitions, the scintillation source can cal framework can be applied to be described as a spatial distriexplore other light-emission phebution of fluctuating dipoles that results the scintillation from a silicon-on-silica nomena, such as harmonic generation and from the radiative transition. Although device bombarded by an electron beam. surface-enhanced Raman spectroscopy, the light emission from fluctuating dipoles Scintillation in the device is emitted by where the understanding of both electron can be modeled, in principle, using a typithe defects in the silica layer (10), and the and photon dynamics is important. Finally, cal electromagnetic field solver that solves silicon layer is designed to provide scintilthe present theoretical framework relies Maxwell’s equations (8), this brute force lation enhancement. They compare results upon the use of reciprocity. It is known approach is computationally costly and from similar scintillators where the silicon that nonreciprocal nanophotonic strucoften impractical. Roques-Carmes et al. layer is uniform with the enhanced vertures can exhibit unusual thermal emissimplify this computation process by exsion where the silicon layer has a lattice sion (12) and cathodoluminescence (13) ploiting electromagnetic reciprocity, which of specially patterned cuts. The scintillaproperties. It may therefore be of interest states that the relationship between a fluction emission from the patterned samples to explore scintillation in nonreciprocal tuating dipole and the resulting electric shows very strong and wavelength-depennanophotonic structures. j field remains the same if their positions dent enhancement. Overall, the patterned REF ERENCES AND NOTES are interchanged (9). Based on this exsample shows up to sixfold enhancement 1. J. A. Sorenson, M. E. Phelps, Physics in Nuclear Medicine ploit, the emission enhancement can then compared with the sample that has the (Grune & Stratton, ed. 2, 1987). be computed by simulating the absorption unstructured silicon layer, with the addi2. P. Lecoq, A. Gektin, M. Korzhik, Inorganic Scintillators for Detector Systems (Springer, 2017). of an electromagnetic plane wave. Finally, tional ability to tune the scintillation spec3. P. Pignalosa, B. Liu, H. Chen, H. Smith, Y. Yi, Opt. Lett. 37, the scintillation can be described by comtra by changing the cut depth. Electronic 2808 (2012). bining emission-enhancement distribution dynamics can also play a role in control4. C. Roques-Carmes et al., Science 375, eabm9293 obtained from photonic simulations with ling the scintillation process. The authors (2022). the power of the scintillation source as obalso measure the scintillation emission in 5. S. Noda, M. Fujita, T. Asano, Nat. Photonics 1, 449 (2007). 6. H. Demers et al., Scanning 33, 135 (2011). tained from electronic simulations. both red and green wavelength ranges. By 7. F. J. García de Abajo, Rev. Mod. Phys. 82, 209 (2010). Based on their framework of theoretichanging either the energy or the power 8. C. Luo, A. Narayanaswamy, G. Chen, J. D. Joannopoulos, cal modeling, Roques-Carmes et al. design of the incident free electrons, the ratio of Phys. Rev. Lett. 93, 213905 (2004). and demonstrate several nanophotonicsgreen to red scintillation peak powers can 9. V. S. Asadchy, M. S. Mirmoosa, A. Diaz-Rubio, S. Fan, S. A. Tretyakov, Proc. IEEE 108, 1684 (2020). enhanced scintillators (see the figure). In be controlled, which can be understood by 10. S. Girard et al., Rev. Phys. 4, 100032 (2019). one set of experiments, they investigate using the rate equations to describe the 11. S. Molesky et al., Nat. Photonics 12, 659 (2018). microscopic transition dynamics. 12. L. Zhu, S. Fan, Phys. Rev. B 90, 220301 (2014). In another set of experiments, Roques13. R. Yu, A. Konečná, F. J. García de Abajo, Phys. Rev. Lett. Ginzton Laboratory, Department of Electrical 127, 157404 (2021). Carmes et al. demonstrate a roughly nineEngineering, Stanford University, Stanford, CA, USA. Email: [email protected] fold enhancement over the measured scin10.1126/science.abn8478 SCIENCE science.org

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C. Thomas Caskey (1938–2022) A visionary architect of genomic medicine By Andrea Ballabio1,2,3,4 and Huda Zoghbi3,4,5

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enowned molecular and human geneticist C. Thomas Caskey died on 13 January. He was 83 years old. Tom transformed biomedical research in both academic medical centers and the pharmaceutical industry, effortlessly moving between the two worlds and catalyzing new ideas and applications. His discovery of trinucleotide repeats and their role in dynamic mutations helped overturn a century’s worth of assumptions about genetic inheritance. A visionary physician-scientist, he also had a gift for nurturing talent and building programs that would themselves redraw the boundaries of scientific possibility. Born in Lancaster, South Carolina, on 22 September 1938, Tom never lost his relaxed southern charm. He studied chemistry at the University of South Carolina for 2 years before transferring into the Duke University School of Medicine. There, he spent a year researching purine biosynthesis and the genetics of gout under the mentorship of physician James B. Wyngaarden before receiving an MD in 1963. In 1965, after completing a residency in internal medicine, he joined geneticist Marshall Nirenberg’s lab at the National Institutes of Health. Tom’s experiments demonstrated the universality of the genetic code from bacteria through mammals and identified the proteins that terminate translation of mRNA. During this time, he mentored Arthur L. Beaudet, Edward Scolnick, and Joseph Goldstein, physicians who later became pioneers in their own right. In 1971, Caskey left for Baylor College of Medicine in Houston, Texas, where he started the division of genetics that eventually became the Department of Molecular and Human Genetics. Although Tom was a physician, he did not overprioritize human genetics—instead, he recruited scientists working in diverse species, so that yeast, fly, mouse, and human genetics researchers were constantly rubbing shoulders in the hallways, at seminars, and at journal clubs. Cross-species collaborations became the norm at Baylor. Tom also had a 1

Telethon Institute of Genetics and Medicine, Pozzuoli, Italy. 2Department of Translational Medicine, University of Naples Federico II, Naples, Italy. 3Neurological Research Institute, Texas Children’s Hospital, Houston, TX, USA. 4 Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX, USA. 5Howard Hughes Medical Institute, Baylor College of Medicine, Houston, TX, USA. Email: [email protected]; [email protected]

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keen sense for which new technologies would be most important in advancing genetic research. For example, he brought in viral gene therapy and sequencing technologies and persuaded Allan Bradley to come all the way from England, bringing embryonic stem cell technology with him. All this helped the department become renowned as a cradle for discoveries. When we joined the faculty in the late 1980s, we benefited tremendously from this intellectual and technological vibrancy. Tom’s early work in enzymology bore fruit in 1982 when he cloned the gene that encodes hypoxanthine-guanine phosphoribosyltransferase, the enzyme whose loss causes gout and Lesch-Nyhan syndrome. His great-

est scientific contribution, however, was the discovery of tri- and tetranucleotide repeats in the genome. These repeats form tracts of variable length in healthy individuals but over a certain threshold can become subject to further expansions. In 1991, three teams (one of which included Tom) showed that fragile X syndrome was caused by an unstable CGG repeat tract that expands on germline transmission. This “dynamic mutation” explained how a disease could become more severe with each generation. We now know of 60 distinct disorders caused by dynamic mutations, including myotonic dystrophy, the mutation for which was discovered by Ying-Hui Fu, then a postdoc in Tom’s lab. Tom also recognized that short tandem repeats could have a socially beneficial use: Because the length of these repeat tracts varies between healthy individuals, they

provide a shortcut for identifying genetic material. He used this approach to identify 32 Gulf War casualties, and the method forms the basis of the Federal Bureau of Investigation’s Combined DNA Index System for identifying suspects in crimes. The Caskey lab contributed to the discovery of more than two dozen human disease genes, but Tom had wider ambitions. He rallied his faculty to each contribute their own skills and interests to mapping discrete regions of the genome. This call to action spurred Richard Gibbs to establish the Baylor College of Medicine Human Genome Sequencing Center, one of the five sites that collaborated to assemble the human genome reference sequence. In 1994, Tom relinquished the position he’d held since 1976 as a Howard Hughes Medical Institute investigator to join Merck Research Laboratories as senior vice president of research, where he incorporated human genetics into drug development. In 2006, he returned to Houston and founded the Institute of Molecular Medicine at the University of Texas Health Science Center, and in 2011 he returned to Baylor and launched one of the first programs in precision medicine. He performed whole-genome sequencing on 1190 volunteers, identifying risk variants that he used to guide interventions to forestall the development of disease. Tom served as president of the American Society of Human Genetics, and in 2021 the society honored him with the William Allan Award. He was also elected to the National Academy of Sciences and the National Academy of Medicine. Despite his stature in the field, his interactions with faculty and the more than 90 postdocs and graduate students he trained at Baylor were characterized by warmth and humor. He could be tough, but he also took pains to give encouragement. We mostly remember the twinkle in his eyes when he asked an unexpected question and walked off, leaving you to ponder what you were missing. Whether or not you figured out what he intended, he always made you think. Tom had a zeal for life. He was an avid sailor and often took his family and friends out on the water. He and Peggy, his wife of 62 years, frequently opened their home for lab and faculty gatherings and invited trainees to celebrate holidays with them. His memorable lab parties usually involved people swimming in his pool and Tom sporting a cowboy hat. Those of us lucky enough to know Tom learned to be more ambitious about improving human health and serving society but, above all, to cherish the people around us. He will be remembered as an innovative scientist, a dedicated mentor, and an enthusiastic man who loved life in all its forms. j 10.1126/science.abo3949

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PHOTO: BAYLOR COLLEGE OF MEDICINE

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P OLICY FORUM RESEARCH ETHICS

Streamlining ethics review for international health research Single-site review means protection and efficiency By Mark A. Rothstein1, Ma’n H. Zawati2, Adrian Thorogood2, Michael J. S. Beauvais2, Yann Joly2, Kyle B. Brothers1, Michael Lang2, Pamela Andanda3, Calvin Ho4, Rosario Isasi5, Jane Kaye6, Won Bok Lee7, Obiajulu Nnamuchi8, Andrea Saltzman9, Bartha Maria Knoppers2

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nternational biomedical research, in which projects span borders and engage participants from multiple countries, has increased substantially during the last several decades. Despite the proven value of large, geographically, and ethnically diverse studies, further advancements are being impeded by the burden of submitting separate, and often numerous, applications for research ethics approval in compliance with country-specific laws or varied policy frameworks. To address this, we see promise in applying the international concept of “adequacy,” contained in the European Union (EU) General Data Protection Regulation (GDPR) (1), to ethics review of international health research. We advocate for countries to publish their prior determinations about the adequacy of ethics review requirements in other countries to enable review by one institutional review board (IRB) or comparable body (“single-site” review) in the researcher’s country, streamlining ethics review while safeguarding the welfare of local research participants. Research ethics rules in nearly every country were developed when health research was small-scale, domestic, and clinical. Some of the most restrictive laws were enacted in response to a history of colonialism (or “ethics dumping”) (2), economic imperialism, or ethically questionable research practices. Adding to these concerns were issues of national sovereignty and the entrenched system of single-country review. There is general agreement about the criteria for research ethics review, but each country has its own procedures. Researchers planning international recruitment of par-

ticipants must first overcome a dearth of information about ethics review in multiple countries. Although some compilations of international laws, regulations, and guidelines are published (3), obtaining accurate and current information about the ethics review requirements of numerous countries remains difficult (4). The lack of easily available resources means that researchers often must retain lawyers or research ethics consultants in their own country—and possibly in the prospective participants’ countries—to discern the substantive and procedural elements of research ethics approvals. This often substantial and unexpected expense can create unnecessary delay. Thus, an essential starting point is ensuring access to continually updated and expertly translated online resources of research ethics materials. Even then, researchers face the prospect of separate ethics reviews in each country. Multiple reviews are arduous, involving substantial and compounding costs and delays without necessarily improving protections for research participants. It is particularly impractical when recruiting small numbers of participants from multiple countries. Furthermore, multiple ethics reviews, even in the same country, are often inconsistent (5). A recent study illustrates challenges that researchers face in such a balkanized system. The authors of this article were part of a team that surveyed laws in 31 diverse countries and detailed how common approaches to ethics review processes could facilitate international direct-to-participant (DTP) genomic research (6) in which researchers use the internet to recruit and enroll research participants, without using physicians, hospitals, or biobanks. As part of that study, we asked legal experts in these countries questions in the context of international DTP genomic research (6). Two conclusions from this survey are of particular interest (recognizing that the opinions of individual legal experts that we engaged might not be shared unani-

mously by others in the surveyed countries). First, most of the experts reported that there was no official legal determination of how research ethics review requirements in their own country applied to foreignbased research. They could at best merely predict how existing laws would be interpreted. Second, experts from only five countries (Australia, Canada, Germany, Japan, and Spain) reported that approval by a review body in the researcher’s country is sufficient, although exceptions may exist for clinical trials. EQUIVALENCY, ADEQUACY, RECIPROCITY Our proposal for single-site ethics review is based on international adoption of three fundamental concepts: equivalency, adequacy, and reciprocity. Equivalency means that the essential standards of ethical research with human participants are substantially equivalent from one country to another in theory and practice. Adequacy means that research ethics review in other countries is adequate to safeguard the interests of research participants and the national interests of their countries. Reciprocity means that one country recognizes the research ethics processes of another country, or two or more countries mutually agree to recognize each other’s research ethics processes. The possibility of eliminating multiple ethics reviews for international research is supported by the considerable equivalence in the national procedures and benchmarks for review of IRBs and similar bodies. Given this compatibility, it should be possible to identify a set of core criteria for appropriate ethics review that, if followed in one country, could be recognized as appropriate for review internationally. For example, the Global Alliance for Genomics and Health (GA4GH) compiled substantive elements and procedures for research ethics review around the globe (7) (see the table). Moreover, there is consistency on the common values governing research ethics that need to be addressed by researchers in their protocols irrespective of jurisdiction (8). These “classical ethical” considerations are endorsed by respected international bodies, including the United Nations Educational, Scientific, and Cultural Organization (UNESCO) (9). The elements include informed consent, privacy/confidentiality, benefit/risk ratio, return of results, commercialization (if applicable), protection of the interests of vulnerable persons/communities, and research integrity and safety.

1

Institute for Bioethics, Health Policy and Law, University of Louisville School of Medicine, Louisville, KY, USA. 2Centre of Genomics and Policy, McGill University Faculty of Medicine and Health Sciences, Montreal, QC, Canada. 3University of Witswatersrand, Johannesburg, South Africa. 4Centre for Medical Ethics and Law and the Department of Law, University of Hong Kong, Pokfulam, Hong Kong, PRC. 5Department of Human Genetics and John P. Hussman Institute for Human Genomics, University of Miami School of Medicine, Miami, FL, USA. 6Oxford University, Oxford, UK. 7 Ewha Law School, Seoul, South Korea. 8Centre for Health, Bioethics and Human Rights, Faculty of Law, University of Nigeria, Enugu, Nigeria. 9Office of Research Subject Protection, The Broad Institute, Cambridge, MA, USA. Email: [email protected] SCIENCE science.org

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Equivalence of international standards and processes makes single-site ethics review a promising alternative to multisite, multicountry review. Single-site ethics review has been shown to be more efficient and consistent on a national basis, including in the United Kingdom (10) and Canada (11). It is now required in the United States (12). An international “adequacy” model, already used in the domain of data protection and international data transfer, could serve to frame, guide, and coordinate decisions as to whether biomedical research ethics review and oversight are essentially equivalent between two jurisdictions. For example, an adequacy decision by the European Commission recognizes that the data protection regime in a country offers an essentially equivalent level of data protection and can be considered as achieving a similar outcome as if Europe’s GDPR (1) were followed. Likewise, under a research ethics adequacy approach, researchers could “have their IRB approvals recognized in another country if the health research norms of both countries are demonstrated to be essentially equivalent, both in terms of their purpose and their effectiveness” (13). In this way the framework of single-site ethics review in the researcher’s country is generalizable and serves to streamline ethics review while protecting the welfare of diverse participants in international health research. We outline four recommendations for an international adequacy model of single-site research ethics review: (i) International research approved by an ethics review body in the researcher’s country should be deemed approved in the participant’s country if the overall ethics review regime in the researcher’s country has been determined to be adequate by the local participant’s country; (ii) a list of countries for which an ethics review undertaken by a competent foreign ethics review body is deemed adequate should be posted on the website of the regulatory authority responsible for the ethical conduct of research with human participants in each country; (iii) regulatory authorities responsible for the ethical conduct of research with human participants should inform ethics review bodies under their jurisdiction of the approval criteria for international health research; and (iv) in applying this framework, special attention should be given to the specific ethical provisions required by the participants’ country as well as the sociocultural traditions or vulnerabilities of various population subgroups in the participants’ country, including minority and Indigenous populations. In assessing these recommendations, a key element is that the approval process begins in the participant’s country. Only if research 826

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regulatory officials in the participant’s country have made a prior determination that ethics review in the researcher’s country is adequate does the researcher-country–based ethics review body have authorization to consider the research protocol. Furthermore, any country may add limitations or conditions to an adequacy decision and require approval of certain types of research in their country. Requirements may include local approval for clinical research, collaboration with a local researcher, community engagement with certain participants, specific consent procedures in accordance with cultural expectations, additional privacy and confidentiality protections, special provisions on data access, a requirement of insurance or other compensation in the event of

Procedural elements of effective ethics review Drawn from (7). • Established norms of conduct, including authority and independence • Resources to carry out the work • Competence of members • Understandable procedures and forms • Equitable treatment of the protocols of all researchers • Attention to vulnerable populations and cultural differences • Record of due diligence • Transparency of decisions • Continuing oversight of approved protocols • Accountability of all reviewers and public authorities

injury, or more general benefit sharing (14). Thus, within this broad framework of equivalent research ethics criteria, countries can require additional features deemed essential to protecting the well-being and interests of participants in their countries. IMPLEMENTATION CHALLENGES Implementation of this proposal will be challenging. Each country would need to formalize legislation, regulations, or professional guidance recognizing the ethics review processes of other countries. Endorsement of the recommendations in the ethical guidelines and best practices of international organizations could generate momentum for global adoption. Some key organizations include the Council of Europe, the Council for International Organizations of Medical Services, the World Health Organization, the Africa Union Development Agency–New Partnership for Africa’s Development, UNESCO,

and the World Medical Association. Funders of international research, such as the Bill & Melinda Gates Foundation and the Wellcome Trust, also could play an important role in harmonizing international standards for the ethical conduct of health research. It is important to recognize that, at least initially, the countries mainly benefiting from single-site ethics review in the researcher’s country are likely to be high-income countries that perform most international health research. Low- and middle-income countries might stand to lose the most if single-site ethics review means a loss of research partnerships and ethics review capacity building (15). Successful implementation strategies could include initial implementation between high-income, major research countries; limiting international ethics review to IRBs and similar bodies that have special training and receive certification to evaluate international research protocols; or phasing in single-site review after a period of systematically comparing the results of ethics review of the same protocol by ethics review bodies in different countries. Ultimately, adoption of a new way of conducting international ethics review will depend on equal measures of altruism, trust, and hope in realizing the possibilities of biomedical research. j REF ERENCES AND NOTES

1. Regulation (EU) 2016/679 of the European Parliament. 2. D. Schroeder, J. Cook, F. Hirsch, S. Fenet, “Ethics Dumping: Introduction,” in Ethics Dumping Case Studies from North-South Research Collaborations, D. Schroeder, J. Cook, S. Fenet, V. Mythuswamy, Eds. (Springer, 2018), pp. 99–106. 3. Office of Human Research Protections, International Compilation of Human Research Standards, www.hhs. gov/ohrp/international/compilation-human-researchstandards/index.html. 4. P. Andanda, J. Wathuta, K. Leising, D. Schroeder, National and International Compliance Tools, A Report for TRUST, http://trust-project.eu/wp-content/uploads/2017/02/ TRUST-664771-National-and-InternationalCompliance-Tools-Final.pdf. 5. D. Resnik, J. Clin. Res. Best Pract. 10, 1 (2014). 6. M. A. Rothstein et al., J. Law Med. Ethics 47, 705 (2019). 7. Global Alliance for Genomics and Health, “Enabling responsible genomic data sharing for the benefit of human health,” www.ga4gh.org. 8. M. H. Zawati et al., J. Law Med. Ethics 47, 582 (2019). 9. UNESCO, https://unesdoc.unesco.org/ark:/48223/ pf0000146180. 10. Royal College of Physicians, Guidelines on the Practice of Ethics Committees in Medical Research with Human Participants (Royal College of Physicians, 2007). 11. J. V. Lavery, M. McDonald, E. M. Meslin, Health Law Rev. 13, 86 (2005). 12. Code of Federal Regulations, Title 45, sec. 46.114. 13. A. Thorogood, M. J. S. Beauvais, Philosophies 6, 93 (2021). 14. E. S. Dove et al., Science 351, 1399 (2016). 15. COVID-19 Clinical Research Coalition, Ethics Review Mutual Recognition and Multinational Research Collaboration in Pandemic Response Settings, (2021); https://covid19crc.org/wp-content/uploads/2021/03/ Covid19-Ethics-Working-Group-Report_FINAL_.pdf. ACKNOWL EDGMENTS

Research support was provided by the U.S. National Institutes of Health. 10.1126/science.abn0675

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2. F. Hu, “Groundwater under pressure” (2015); www.chinawaterrisk.org/resources/analysis-reviews/ groundwater-under-pressure/. 3. China Institute of Geo-Environment Monitoring, “Map of land subsidence in China” (2019). 4. Y. Luo, Bull. Chin. Acad. Sci. 31, 133 (2016). 5. W. Meng et al., Ocean Coast. Manage. 146, 50 (2017). 6. K. Ravilious, “How vulnerable is China’s water?” Physics World (2019). 7. C. Dagbegnon, S. Djebou, V. P. Singh, Environ. Soc. Psychol. 1, 16 (2016). 8. The State Council of the People’s Republic of China. “Regulation on Groundwater Management (000014349/2021-00106)” (2021). 10.1126/science.abn8377

Transparency crucial to Paris climate scenarios

LET TERS Groundwater overexploitation in China has led to rapid declines in the water table, drying up rivers like this one.

Edited by Jennifer Sills

PHOTO: CHUNMIAO ZHENG

Plans to protect China’s depleted groundwater Groundwater is a hidden resource that can store 100 times as much as global freshwater lakes and rivers (1). In China, groundwater serves as the primary source for drinking water for 70% of the population (2). Historically, China has lagged behind developed countries in managing and protecting groundwater. Over the past several decades, China has rapidly depleted groundwater reserves (2). Overexploitation of groundwater for domestic, agricultural, and industrial uses, exacerbated by climate change, has resulted in about 920,000 km2 with substantial land subsidence (3) and more than 10,000 km2 of coastal areas affected by seawater intrusion (4). It has also contributed to the loss of more than 16,000 km2 of wetlands (5) and to more than half of the country’s 50,000 rivers drying up (6). Overuse has left China’s groundwater in a perpetual state of crisis (7). In November 2021, Chinese Premier Li Keqiang signed the Regulation on Groundwater Management (8). The legislation was created to comprehensively and explicitly address groundwater-related issues, including investigation and planning, monitoring, risk assessment, overdraft control, pollution prevention, site remediation, regulatory oversight, and sustainable management. The plan requires SCIENCE science.org

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ongoing consideration of groundwater quantity and quality and their relations to ecosystems, climate change, and sustainability. National coordination and enforcement will facilitate the implementation of management strategies, and clear division of responsibilities and jurisdictions for different government agencies will help to minimize bureaucratic red tape. These changes mark an important first step to sustainable groundwater management. To ensure that China’s efforts toward sustainable groundwater supplies are successful, the government should mandate equitable funding to support groundwater research and protection. For example, out of several hundred “state key laboratories” in science, engineering, and medicine, not one is currently devoted primarily to groundwater. Enactment of protective legislation should go hand-in-hand with strict enforcement of existing regulations. Finally, datasharing in the field of groundwater should become a norm rather than an exception to promote management transparency and scientific advances. Chunmiao Zheng* and Zhilin Guo* State Environmental Protection Key Laboratory of Integrated Surface Water-Groundwater Pollution Control, School of Environmental Science and Engineering, Southern University of Science and Technology, Shenzhen, China. *Corresponding author. Email: zhengcm@sustech. edu.cn; [email protected] REF ERENCES AND NOTES

1. R. Taylor et al., “Groundwater and global hydrological change-current challenges and new insight,” IAHS Publ. 338 (2010), pp. 51–61.

In their Policy Forum “Can updated climate pledges limit warming well below 2°C?” (5 November 2021, p. 693), Y. Ou and coauthors explain that the updated pledges submitted as part of the Paris Agreement process, although an improvement, will only result in a ~33% chance of staying within 2°C of warming. We agree with Ou et al. that more ambition is required, but we think even the low chance of success they estimate is overly optimistic. The mitigation pathways based on Paris Agreement pledges lack transparency and immediacy, making them difficult to evaluate and decreasing the chances of success. The updated pledges, if executed as written, will result in negligible global emission reductions of 1% by 2030, according to Ou et al. Substantive reductions are postponed until after 2030 on the assumption that countries will fulfill their softer commitment to “long-term strategies.” In line with earlier studies using integrated assessment models (1), these strategies heavily depend on negative-emissions technologies. For example, US fossil fuels and industry emissions are expected to fall from 2.7 GtCO2 to –1.1 GtCO2 between 2030 and 2050 according to the “Updated pledgesContinued ambition” scenario proposed by Ou et al. However, implementing negative-emissions technologies at such a large scale remains highly speculative and would present serious challenges to other sustainability dimensions (2). Analyses of this nature need to be transparent about the extent to which negative-emissions technologies are used. Only then can we evaluate the inherent risk of this goal not being achieved. Other uncertainties merit structural attention as well. An energy transition to low-carbon alternatives could result in a lower average energy return, leading to 25 FEBRUARY 2022 • VOL 375 ISSUE 6583

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additional energy costs and indirect emissions (3). Moreover, modeled transitions rely on decoupling gross domestic product and energy at a faster rate than historical trends, which underestimates rebound effects caused by energy-efficiency policies (4). In addition, differing levels of pledge ambition could lead to carbon leakage, where emissions are transferred to countries with weaker policies (5). The extent to which these neglected uncertainties are captured in current and future integrated assessment model studies of the Paris Agreement pathways needs to be transparent and, ideally, quantified. Lewis King1*, Jeroen van den Bergh1,2,3, Giorgos Kallis1,2 1

Institute of Environmental Science and Technology, Universitat Autonoma de Barcelona, 08193 Bellaterra, Catalonia, Spain. 2ICREA, 08010 Barcelona, Catalonia, Spain. 3Vrije Universiteit Amsterdam, 1081 HV Amsterdam, The Netherlands. *Corresponding author. Email: [email protected] REFERENCES AND NOTES

1. A. A. Fawcett et al., Science 350, 1168 (2015). 2. K. Anderson, G. Peters, Science 354, 182 (2016). 3. L. C. King, J. C. J. M. van den Bergh, Nat. Energ. 3, 334 (2018). 4. P. E. Brockway, S. Sorrell, G. Semieniuk, M. K. Heun, V. Court, Renew. Sustain. Energ. Rev. 141, 110781 (2021). 5. L. C. King, J. C. J. M. van den Bergh, Clim. Change 165, 52 (2021). 10.1126/science.abn7998

Response King et al. raise important issues, several of which pertain to the broader policy discourse surrounding international climate negotiations and countries’ climate pledges rather than the modeling conducted in our Policy Forum. We agree with King et al. that the updated Paris Agreement pledges could paint an overly optimistic picture of the future, especially if their success depends on postponing deeper reductions until after 2030. To illustrate a less-optimistic future, our Policy Forum includes scenarios showing what would happen if countries continued

to implement current policies alone. The “Current policy” scenarios in the Policy Forum result in less than a 10% chance of limiting global warming to below 2°C this century, whereas the “Updated pledges” scenarios result in at least a 33% chance of achieving the same temperature goal. Additional policy measures could help bridge emission gaps between current policies, updated pledges, and the global emission levels needed to cost-effectively achieve the Paris Agreement’s climate goals (1). We also agree with King et al. that greater near-term ambition is necessary, particularly to set up the technological, political, and financial infrastructures required to achieve the long-term strategies and net-zero pledges (2). Delaying emission reductions would substantially reduce the likelihood of achieving the Paris temperature goal (3) and could prove to be very expensive (4). However, we disagree that the updated 2021 pledges result in negligible global emission reductions. Our Policy Forum suggests that the updated pledges alone—if successfully implemented—could result in a reduction of 2030 global greenhouse gas emissions of about 6.6 GtCO2 (12%) compared with the 2015 pledges. The United Nations Environment Programme suggests reductions of 4 GtCO2 (7.5%) (5). The “Updated pledges-Continued ambition” scenario in our Policy Forum assumes that countries with net-zero pledges achieve those pledges in the specified target years. Achieving net-zero pledges will require large-scale deployment of negative-emissions technologies (6, 7). Our study assumes the availability of bioenergy with carbon capture and storage (BECCS) and direct air capture (DAC) technologies in addition to terrestrial sinks and makes conservative assumptions about their deployment compared to the literature (7). Our assumptions about BECCS and DAC are transparently documented in several publications [e.g., (8, 9)].

NEXTGEN VOICES: SUBMIT NOW

Rules every PI should follow Add your voice to Science! Our new NextGen Voices survey is now open: Imagine that you can write one rule that every principal investigator (PI) must follow to improve the experience of young scientists in their lab. What rule would you enact? To submit, go to www.science.org/nextgen-voices Deadline for submissions is 4 March. A selection of the best responses will be published in the 1 April issue of Science. Submissions should be no more than 50 words. Anonymous submissions will not be considered.

Moreover, the entire model code and data files used in our study are publicly available (10). Future research should explore the implications of alternative assumptions about the type and scale of negativeemissions technologies. Our Policy Forum addressed uncertainties in the climate system, but we only focused on one source of uncertainty in emissions trajectories: stringency of climate policy. The minimum decarbonization rate assumption (2% per year) in our “Continued ambition” scenarios is on the conservative side of historical trends [fig. S2 in (11)] and conservative compared to developed countries with decarbonization policies (tables S14 to S17 in our Policy Forum). By contrast, our “Increased ambition” scenarios assume a higher minimum decarbonization rate (5%), which is on the higher end of historically observed rates [fig. S2 in (11)]. Many other uncertainties—including and beyond those highlighted by King et al.—could affect future emissions trajectories (12). Future research should also explore the implications of these variables. Yang Ou1, Gokul Iyer1, James Edmonds1, Allen Fawcett2, Nathan Hultman3, Jim McFarland3, Stephanie Waldhoff1, Matthew Gidden4,5, Haewon McJeon1* 1

Joint Global Change Research Institute, Pacific Northwest National Laboratory and University of Maryland, College Park, MD 20740, USA. 2US Environmental Protection Agency, Washington, DC 20004, USA. 3Center for Global Sustainability, School of Public Policy, University of Maryland, College Park, MD 20742, USA. 4Climate Analytics, Berlin, Germany. 5International Institute for Applied Systems Analysis, Laxenburg, Austria. *Corresponding author. Email: [email protected] REF ERENCES AND NOTES

1. L. B. Baptista et al., Glob. Environ. Change 73, 102472 (2022). 2. G. Iyer et al., Nat. Clim. Change 7, 871 (2017). 3. Climate Action Tracker, “Glasgow’s 2030 credibility gap: Net zero’s lip service to climate action,” Warming Projections Global Update November 2021 (2021). 4. G. C. Iyer et al., Environ. Res. Lett. 10, 125002 (2015). 5. United Nations Environment Programme, “Emissions gap report 2021: The heat is on—a world of climate promises not yet delivered” (2021). 6. G. Iyer et al., Energ. Clim. Change 2, 100043 (2021). 7. Intergovernmental Panel on Climate Change, “Global warming of 1.5°C” (2018); https://www.ipcc.ch/sr15/. 8. J. Fuhrman et al., Environ. Res. Lett. 16, 114012 (2021). 9. M. Muratori et al., Environ. Res. Lett. 11, 095004 (2016). 10. Y. Ou, “Source code and data for Ou et al. (2021) Updates to Paris climate pledges improve chances of limiting global warming to well below 2°C [Data set],” Zenodo (2021). 11. A. A. Fawcett et al., Science 350, 1168 (2015). 12. L. Clarke et al., in Climate Change 2014: Mitigation of Climate Change. Contribution of Working Group III to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change, O. Edenhofer et al., Eds. (Cambridge University Press, 2014), chap. 6.

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Medical personnel in an overcrowded intensive care unit battle SARS-CoV-2 in critically ill patients.

IMMUNOLOGY

Why do people die from COVID-19? Autoantibodies that neutralize type I interferons increase with age By Paul Bastard1,2,3

PHOTO: ANDREW TESTA/PANOS PICTURES

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he past 2 years have witnessed the infection of millions of people with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). The course of infection is highly variable. Some young patients have died, while several centenarians, having already lived through the 1918 influenza pandemic, have survived SARS-CoV-2 infection—without experiencing severe respiratory symptoms. These anecdotal observations belie a key risk factor that emerged early on: The risk of death doubles for every 5 years of age (1, 2). Comorbid conditions have also been shown to affect outcome, but with a lower relative risk (3). Risk factors are not causal explanations, and SCIENCE science.org

the question remains: Why is SARS-CoV-2 infection fatal in more than 10% of people over 80 years old but in fewer than 0.001% of individuals below 18 years old? Since the onset of the pandemic, the COVID Human Genetic Effort (CHGE) has recruited patients infected with SARS-CoV-2 who exhibit either mild infection or severe and/or critical COVID-19 pneumonia (i.e., requiring oxygen supplementation) (4). We sequenced these patients’ exomes to test our hypothesis that some individuals with lifethreatening COVID-19 have underlying inborn errors of immunity (IEI) (5). Mutations in interferon regulatory factor 7 (IRF7) are already known to underlie severe viral infections such as fulminant influenza pneumonia (6). In patients with life-threatening COVID-19

pneumonia, including previously healthy adults, we found IEI that affect Toll-like receptor 3 (TLR3)– and IRF7-dependent type I interferon (IFN) immunity with complete or autosomal-recessive IRF7 or IFN-a/b receptor subunit 1 (IFNAR1) deficiency. A parallel unbiased genome-wide approach found lossof-function variants of X-linked gene TLR7 in more than 1% of men with life-threatening COVID-19, leading to deficient type I IFN production (7). On this genetic basis, could other types of type I IFN pathway deficiencies account for life-threatening COVID-19 in other patients (8)? 1

Laboratory of Human Genetics of Infectious Diseases, Imagine Institute, University of Paris and INSERM U1163, Paris, France. 2The Rockefeller University, New York, NY, USA. 3Department of Pediatrics, Necker Hospital for Sick Children, AP-HP, Paris, France. Email: [email protected] 25 FEBRUARY 2022 • VOL 375 ISSUE 6583

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be performed at any time (5, 9, 10, 12). Auto-Ab–positive patients should be vaccinated against SARS-CoV-2 as a matter of priority, but not with a live attenuated vaccine (13, 14). In cases of infection, these patients should be hospitalized and would benefit from early treatment with antiviral compounds, monoclonal antibodies (15–17), and/or IFN-b, provided they have neither pneumonia nor auto-Abs against IFN-b (18). Early administration of type I IFNs in patients infected with SARS-CoV-2 could prevent viral growth and uncontrolled infection, which can lead to a cytokine storm and life-threatening COVID-19. Other treatments designed to enhance the type I IFN pathway, or to replicate its antiviral effects, are of potential interest for the treatment of SARS-CoV-2 infection. Beyond COVID-19, many other viral diseases increase in severity with age, suggesting a possible role of auto-Abs against type I IFNs in their severity. We have shown previously that auto-Abs that neutralize type I IFNs underlie one-third of adverse reactions to the live-attenuated yellow fever virus vaccine (11). It therefore appears likely that these auto-Abs also underlie other viral infections, especially those for which severity increases with age. Influenza affects millions of people worldwide every year, causing between 200,000

and 650,000 deaths (19). It remains unclear why deaths from influenza disproportionately affect the elderly (20), but some of these deaths could be due to autoAbs that neutralize type I IFNs. Why does the prevalence of auto-Abs against IFNs increase with age? The answer might provide hints to targeted treatments for preventing auto-Abs from being produced in the first place, or for their targeted removal prior to infection. It might also help to explain other issues, from the redundancy of type I IFNs to the causes of various autoimmune diseases. j REF ERENCES AND NOTES

1. 2. 3. 4. 5. 6. 7. 8. 9. 10. 11. 12. 13. 14. 15. 16. 17. 18. 19. 20.

A. T. Levin et al., Eur. J. Epidemiol. 35, 1123 (2020). M. O’Driscoll et al., Nature 590, 140 (2021). E. J. Williamson et al., Nature 584, 430 (2020). J. L. Casanova, H. C. Su, Cell 181, 1194 (2020). Q. Zhang et al., Science 370, abd4570 (2020). M. J. Ciancanelli et al., Science 348, 448 (2015). T. Asano et al., Sci. Immunol. 6, abl4348 (2021). J. L. Casanova, L. Abel, Science 374, 1080 (2021). C.-L. Ku, C.-Y. Chi, H. von Bernuth, R. Doffinger, Hum. Genet. 139, 783 (2020). P. Bastard et al., Science 370, abd4585 (2020). P. Bastard et al., J. Exp. Med. 218, e20210554 (2021). P. Bastard et al., Sci. Immunol. 6, abl4340 (2021). L. Sanchez-Felipe et al., Nature 590, 320 (2021). P. Bastard et al., J. Exp. Med. 218, e20202486 (2021). P. Chen et al., N. Engl. J. Med. 384, 229 (2021). D. M. Weinreich et al., N. Engl. J. Med. 384, 238 (2021). E. M. N. Ferré et al., Front. Immunol. 12, 720205 (2021). P. Bastard et al., J. Clin. Immunol. 41, 931 (2021). J. Paget et al., J. Glob. Health 9, 020421 (2019). F. Krammer et al., Nat. Rev. Dis. Primers 4, 3 (2018). 10.1126/science.abn9649

GRAND PRIZE WINNER

Paul Bastard Paul Bastard, MD, PhD, is currently working as a chief resident in the Department of Pediatrics at the Necker Hospital for Sick Children (AP-HP, Paris, France) while also doing research in the Necker branch of the laboratory of Jean-Laurent Casanova, located at the Imagine Institute (University of Paris and INSERM) and the Rockefeller University (New York, USA). His research focuses on the genetic and immunological determinants of severe viral diseases, including the causes and consequences of autoantibodies against type I interferons. FINALIST

Scott Biering Scott Biering received undergraduate degrees from the University of California, Los Angeles, and a PhD in microbiology from the University of Chicago. He is currently a postdoctoral scholar at the University of California, Berkeley, in the laboratory of Eva Harris. His present research investigates the role of viral proteins like flavivirus nonstructural protein 1 (NS1) and SARS-CoV-2 spike (S) in inducing viral pathogenesis and promoting viral dissemination. www.science.org/doi/10.1126/science.abn9651 FINALIST

Lisa Wagar Lisa Wagar received a BSc from the University of Ontario Institute of Technology and a PhD from the University of Toronto. After completing her postdoctoral fellowship at Stanford University, she started her laboratory in 2020 in the Department of Physiology and Biophysics at the University of California, Irvine, where she is currently an assistant professor. Her research focuses on translational human immunology and the use of organoids to understand the complex interactions that occur between immune cells upon vaccination and infection in humans. www.science.org/doi/10.1126/science.abn9652 science.org SCIENCE

PHOTOS: (TOP TO BOTTOM) COURTESY OF QUENTIN LEMAIRE/INSTITUT IMAGINE; COURTESY OF SCOTT BIERING; ANDREW SORN

Autoantibodies (auto-Abs) have been described for IFN-g, interleukin-6 (IL-6), IL17A, and IL-17F and associated with susceptibility to infection (9). We first tested for the presence of auto-Abs in a cohort of 987 individuals with critical COVID-19 compared with more than 663 asymptomatic patients (10). In patients with critical COVID-19, 10% had immunoglobulin G (IgG) auto-Abs that neutralized high amounts of IFN-v and/or the 13 individual types of IFN-a. Further, these auto-Abs prevented IFN-a2 from blocking SARS-CoV-2 in vitro. In autoimmune polyglandular syndrome type-1 (APS-1), affected individuals produce auto-Abs against type I IFNs from early childhood onward. Among a group of APS-1 patients, aged 8 to 48 years, infected with SARS-CoV-2, we found that most were hospitalized for COVID-19 pneumonia, with a fatal outcome for 18% (11). In a separate study of over 4000 patients with severe and/or critical COVID-19, we detected auto-Abs that neutralized more physiological concentrations of IFN-a2 and/or IFN-v in over 15% of patients with critical COVID-19 pneumonia, including more than 20% of patients over 80 years, and ~20% of those who died (12). Notably, another 1% of the patients only had auto-Abs against IFN-b. When we looked at a group of 34,000 uninfected individuals, we found that the prevalence of auto-Abs that neutralized high concentrations of type I IFNs increased markedly with age. AutoAbs were present in 0.18% of those 18 to 69 years, 1.1% of those 70 to 80 years, and 3.4% of those over 80 years. The proportion of patients that produced auto-Abs neutralizing physiological concentrations (i.e., 100-fold lower) was even greater, with 1% of those under 70 years, 2.3% of those 70 to 80 years, and 6.4% of those over 80 years. The findings outlined here provide clues to the reasons why COVID-19 is fatal for some individuals 70 years and older (8). The presence of preexisting auto-Abs against type I IFNs can account for severe disease in some older individuals, as it does in many younger patients presenting with life-threatening COVID-19. Since discovering the role of auto-Abs to type I IFNs in COVID-19 in 2020, I have focused on leading the studies of these auto-Abs in our laboratory and performing studies on COVID-19 as part of the effort led by Qian Zhang and Jean-Laurent Casanova within the CHGE (4). Our observations have several important medical implications: Patients infected with SARS-CoV-2 could be tested for auto-Abs against type I IFNs (e.g., IFN-a2, IFN-v, IFN-b), and in individuals in at-risk groups (e.g., people 70 years and older, or patients with autoimmune conditions), these tests could

PRIZE ES SAY FINALIST

Scott Biering

PHOTO: COURTESY OF SCOTT BIERING

Scott Biering received undergraduate degrees from the University of California, Los Angeles, and a PhD in microbiology from the University of Chicago. He is currently a postdoctoral scholar at the University of California, Berkeley, in the laboratory of Eva Harris. His present research investigates the role of viral proteins like flavivirus nonstructural protein 1 (NS1) and SARSCoV-2 spike (S) in inducing viral pathogenesis and promoting viral dissemination. www.science. org/doi/10.1126/science.abn9651

IMMUNOLOGY

One antibody to treat them all Conserved flavivirus protein holds potential as target for versatile vaccines and therapies By Scott B. Biering

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he Flaviviridae are a family of medically important viral pathogens that include dengue virus serotypes 1 to 4 (DENV1 to DENV4) as well as Zika virus (ZIKV), West Nile virus (WNV), and yellow fever virus (YFV). Together, these mosquito-borne human pathogens impose a tremendous global disease burden (ranging from nonsevere to potentially fatal cases) with devastating economic effects (1). Almost half of the world’s population lives within the tropical and subtropical habitats of the Aedes mosquito vectors that transmit these viruses. As global temperatures continue to climb, the habitats of Aedes will expand further, resulting in even more people being at risk for flavivirus infection. Thus, the development of therapeutics and vaccines to treat or prevent severe flavivirus infections is urgently needed. There are currently no flavivirus therapeutics available, and the lone licensed dengue vaccine, Dengvaxia, is approved only for individuals with preexisting DENV immunity because of the risk of predisposing DENV-naïve recipients to severe disease, presumably from antibodydependent enhancement (ADE) (2, 3). This risk of vaccine-induced ADE is a problem for all current dengue vaccine candidates because they target the envelope (E) protein, making the production of a vaccine challenging. Targeting other viral proteins that contribute to severe disease is now a major avenue of investigation (4). Further, a pan-flavivirus therapeutic or vaccine directed to a conserved viral protein critical for disease is highly attractive given the prevalence of multiple flaviviruses in many Aedes-endemic areas. Previous work from my team’s laboratory and others has implicated the flavivirus nonstructural protein 1 (NS1) as such a target (5, 6). NS1 is well conserved among flaviviruses, exhibiting 20 to 40% identity and 60 to 80% similarity. This protein is essential for viral replication as an intracellular dimer and is Division of Infectious Diseases and Vaccinology, School of Public Health, University of California, Berkeley, Berkeley, CA 94720, USA. Email: [email protected]

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secreted from infected cells as a hexamer containing lipid cargo (7, 8). Secreted NS1 circulates in the blood of infected individuals, where it is used clinically for diagnosis and as a biomarker of disease severity (9). NS1 also functions as a virulence factor through interactions with immune cells, leading to the secretion of proinflammatory and vasoactive cytokines as well as interactions with endothelial cells, which result in endothelial barrier dysfunction and vascular leak (5, 6, 10–12). A cytokine storm and vascular leak are hallmarks of severe DENV infection (13). My colleagues and I have shown that multiple flavivirus NS1 proteins can trigger vascular leak independently of viral infection (14). Further, immunization and passive transfer of anti-NS1 antibodies protects mice from lethal flavivirus challenge, making NS1 a promising target for therapeutic intervention against pan-flavivirus infection with no risk of ADE (5, 15, 16). In 2021, we published a proof of concept for achieving pan-flavivirus protection, reporting the structural basis of protection of a pan-flavivirus anti-NS1 monoclonal antibody (mAb) 2B7 (17). This antibody was isolated from mice immunized with DENV2 NS1 as part of an immunology course taught at the University of California, Berkeley, by P. Robert Beatty in conjunction with the laboratory of Eva Harris more than 20 years ago. Today, our laboratory and many others frequently use 2B7 as a molecular tool to study DENV. As the role of flavivirus NS1 in promoting pathogenesis became apparent, we investigated whether 2B7 could protect against lethal vascular leak syndrome in our mouse model and found that it did (17). To investigate the mechanism by which 2B7 inhibits NS1 pathogenesis, we teamed up with Janet Smith, an expert NS1 structural biologist at the University of Michigan, to resolve a crystal structure of NS1 complexed with 2B7. We reasoned that visualizing the interaction between NS1 and 2B7 could elucidate why 2B7 was protective and potentially how NS1 contributes to disease. Structures of DENV NS1 in complex with 2B7 revealed the possibility that 2B7 may inhibit two domains of NS1 at once. Flavivirus NS1 has three domains, including the amino-terminal β-roll, the wing do25 FEBRUARY 2022 • VOL 375 ISSUE 6583

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main, and the carboxyl-terminal β-ladder (18). The crystal structure of NS1 complexed with 2B7 revealed that 2B7 bound the β-ladder directly but at an angle so that 2B7 ended up blocking the wing domain as well (17). This structure predicted that 2B7 would inhibit the NS1 β-ladder domain to which it bound while indirectly hindering the wing domain from interacting with endothelial cells. We tested this prediction by producing recombinant NS1 proteins with mutations in the β-ladder or wing domains and found that these were defective in mediating pathology. We concluded that 2B7 simultaneously blocked residues in the wing domain of NS1 critical for cell binding as well as directly binding to residues in the β-ladder essential for pathogenesis downstream of cell binding (17). Continued examination of 2B7 and its NS1 binding site revealed that this domain is highly conserved among flaviviruses. We tested whether 2B7 bound to diverse flavivirus NS1 proteins and found that 2B7 bound strongly to NS1 proteins from multiple flaviviruses, including DENV1

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to DENV4, ZIKV, and WNV (17). The possibility that the strong flavivirus crossreactivity of 2B7 would confer crossflavivirus protection against NS1 pathogenesis warranted further study. We conducted in vitro endothelial dysfunction assays and in vivo lethal flavivirus challenge experiments, revealing that 2B7 inhibited DENV, ZIKV, and WNV NS1 in vitro and was protective in in vivo lethal challenge models of both DENV and ZIKV. Years of research initiated by multiple laboratories culminated in our revealing not only critical domains for NS1 pathogenesis but also a highly conserved flavivirus epitope within the NS1 β-ladder, with the potential to serve as a molecular road map for the rational design of NS1-targeted therapeutics. Therapeutic approaches focused on NS1 are a viable alternative strategy to targeting the E protein, given the risk of ADE, and focusing on highly conserved sites within NS1 can achieve flavivirus cross-protection. Further, antagonizing multiple domains of NS1 simultaneously may achieve greater protective efficacy. Ultimately, our study of

2B7 holds the potential to shift the current flavivirus vaccine and therapeutic design paradigm to one that incorporates NS1 and prompts further examination of simultaneous cross-protection against multiple flavivirus infections. j REF ERENCES AND NOTES

1. T. C. Pierson, M. S. Diamond, Nat. Microbiol. 5, 796 (2020). 2. S. Sridhar et al., N. Engl. J. Med. 379, 327 (2018). 3. L. C. Katzelnick et al., Science 358, 929 (2017). 4. D. A. Muller, P. R. Young, Antiviral Res. 98, 192 (2013). 5. P. R. Beatty et al., Sci. Transl. Med. 7, 304ra141 (2015). 6. N. Modhiran et al., Sci. Transl. Med. 7, 304ra142 (2015). 7. I. Gutsche et al., Proc. Natl. Acad. Sci. U.S.A. 108, 8003 (2011). 8. P. Scaturro, M. Cortese, L. Chatel-Chaix, W. Fischl, R. Bartenschlager, PLOS Pathog. 11, e1005277 (2015). 9. S. A. Paranavitane et al., BMC Infect. Dis. 14, 570 (2014). 10. H. Puerta-Guardo, D. R. Glasner, E. Harris, PLOS Pathog. 12, e1005738 (2016). 11. D. R. Glasner et al., PLOS Pathog. 13, e1006673 (2017). 12. C. Wang et al., PLOS Pathog. 15, e1007938 (2019). 13. S. B. Halstead, Lancet 370, 1644 (2007). 14. H. Puerta-Guardo et al., Cell Rep. 26, 1598 (2019). 15. D. A. Espinosa et al., J. Immunol. 202, 1153 (2019). 16. A. C. Brault et al., Sci. Rep. 7, 14769 (2017). 17. S. B. Biering et al., Science 371, 194 (2021). 18. D. L. Akey et al., Science 343, 881 (2014). 10.1126/science.abn9651

science.org SCIENCE

PRIZE ES SAY FINALIST

Lisa Wagar

PHOTO: ANDREW SORN

Lisa Wagar received a BSc from the University of Ontario Institute of Technology and a PhD from the University of Toronto. After completing her postdoctoral fellowship at Stanford University, she started her laboratory in 2020 in the Department of Physiology and Biophysics at the University of California, Irvine, where she is currently an assistant professor. Her research focuses on translational human immunology and the use of organoids to understand the complex interactions that occur between immune cells upon vaccination and infection in humans. www.science.org/doi/10.1126/ science.abn9652

IMMUNOLOGY

Small centers of defense Deciphering immune responses to viruses and vaccines using human tonsil organoids By Lisa Wagar

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he investigation of how the specialized microenvironment of lymphoid tissues regulates adaptive immune responses forms the foundation of my laboratory’s research. At present, I am using human tonsil organoids to predict immunogenicity and immunodominance for vaccines and infectious diseases and then leveraging this new information to improve vaccine design. We are also using tumor organoids (derived from primary human biopsies or excisional surgeries) to investigate the dynamics of tumor– immune cell interactions to dissect the mechanisms by which immunotherapies contribute to tumor control. At present, there are two major challenges that limit our ability to rationally design new immune therapeutics for humans. First, although numerous animal models exist to study adaptive immunity, translating these foundational discoveries into vaccines and immunotherapies remains inefficient. Vaccine efficacy for some of the most well-studied human pathogens (e.g., HIV, Mycobacterium tuberculosis, Plasmodium falciparum, influenza) ranges from 0 to 60%, indicating our inability to predict in vivo immunogenicity on the basis of preclinical data. The second major challenge is that most preclinical studies fail to adequately account for the extent of interindividual immune variation. I have studied the effects of demographic and environmental factors (e.g., age, sex, immune history, microbial environment) on human adaptive immunity and repeatedly found that they play a crucial role (1–3). Studying this variability can help us to understand why some people respond differently to the same drug as well as to develop more broadly effective immune therapeutics. Immune organoids are an optimal strategy to overcome these challenges because they enable us to study the factors that contribute to adaptive immunity in a high-throughput way while controlling for interindividual variation. Organoid technologies have revolutionized our ability to study complex tissues Institute for Immunology, University of California, Irvine, Irvine, CA 92697, USA. Email: [email protected]

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in a physiologically relevant microenvironment. Immune organoid models offer a distinctive opportunity to track the early events in lymphoid tissues that lead to protective responses. In the laboratory, we use tonsils as a source of accessible lymph node–like tissues from humans. Tonsillectomy surgeries are common, and the excised tissue is usually discarded. Lymph nodes are one of the most important tissue types for understanding the maturation of vaccine-induced adaptive immunity. Tonsils are exposed to both respiratory and alimentary antigens and are a key access point for studying the response to both oral and nasal vaccines. We developed an immune organoid model, derived from primary human lymphoid tissues (principally tonsils but also lymph nodes and spleen), to improve the translational value of preclinical vaccine studies and to increase our appreciation of how interindividual differences contribute to immune variation (4). Our organoids are derived from tonsil tissue collected from children (≥2 years old) and adults of ethnically diverse backgrounds, with males and females represented equally. Tonsils are collected from relatively healthy individuals, but we do not exclude those with common conditions such as diabetes and heart disease. We are now screening a large panel of US Food and Drug Administration–approved vaccines in tonsil organoids to build an integrated model of vaccine immunogenicity and make predictions about the magnitude and quality of the response in people. Previous techniques for producing in vitro models of human adaptive immunity, though successful, have not been widely adopted because of reliance on specialized equipment, challenging technical protocols, poor throughput, a lack of evidence for antigen-specific responses, and/or the absence of cells known to be crucial to important features of adaptive immunity (5–12). Contrary to previous immune organoid methods, our tonsil organoid system holistically captures the original cell composition and complete functional capabilities of donor tissues. Research published last year details how these immune organoids respond to influenza and other viral vaccines and patho25 FEBRUARY 2022 • VOL 375 ISSUE 6583

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gens (4). The organoid cultures recapitulate the key features of an adaptive immune response, including T and B cell activation and differentiation, antigen-specific T and B cell expansion, somatic hypermutation, class switching, and specific antibody secretion. Major advantages of the organoid system are that both cellular and humoral immunity can be studied simultaneously and longitudinally and that hundreds of conditions can be tested on a single individual’s cells, revealing intra- and interindividual sources of immune-response variance. We showed that tonsil-derived immune organoids stimulated with vaccines produce antibody responses. Further, using B cell receptor repertoire analysis, we demonstrated antigen-driven B cell maturation through germinal centers within the organoids. The role of T cell help can also be quantified because T follicular helper cells, which are critical for B cell selection; T cell activation; and antigen-specific CD8 T cell expansion were well recapitulated in the organoids.

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My laboratory is now using immune organoids to study the human adaptive immune response to vaccines and infectious diseases—including influenza, Epstein Barr virus, and severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2)—to understand why some individuals respond better than others to a given antigen. Interindividual variation in the magnitude and quality of the antibody response is observable, and we are using clinical and demographic data to explain this variability. The spatial organization of lymphoid tissues plays a key role in orchestrating adaptive immune responses by regulating what cell types are sufficiently proximal to interact and signal one another. The germinal center, where B cells undergo selection and affinity maturation, is structurally complex. The formation and dissolution of germinal centers is dynamic, with changes occurring within minutes and across multiple days. Because some features of the germinal center are preserved in organoid cultures,

we have an unprecedented opportunity to visualize the dynamics of these structures in human samples. Our long-term goal for immune organoid development is to use them to investigate the mechanisms involved in human adaptive immune responses, enable more informed decision-making about what drugs to take to clinical trial, and accelerate vaccine design. j REF ERENCES AND NOTES

1. L. E. Wagar et al., Front. Immunol. 10, 2239 (2019). 2. L. E. Wagar et al., PLOS ONE 6, e28063 (2011). 3. L. E. Wagar, B. Gentleman, H. Pircher, J. E. McElhaney, T. H. Watts, PLOS ONE 6, e23698 (2011). 4. L. E. Wagar et al., Nat. Med. 27, 125 (2021). 5. W. Béguelin et al., Nat. Commun. 8, 877 (2017). 6. A. M. Byers, T. M. Tapia, E. R. Sassano, V. Wittman, Biologicals 37, 148 (2009). 7. C. Giese, U. Marx, Adv. Drug Deliv. Rev. 69-70, 103 (2014). 8. C. Giese et al., Artif. Organs 30, 803 (2006). 9. I. Kuzin et al., Biotechnol. Bioeng. 108, 1430 (2011). 10. A. Purwada, A. Singh, Nat. Protoc. 12, 168 (2017). 11. A. Purwada et al., Biomaterials 198, 27 (2019). 12. A. Purwada et al., Biomaterials 63, 24 (2015). 10.1126/science.abn9652

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Pushing the Boundaries of Knowledge As AAAS’s first multidisciplinary, open access journal, Science Advances publishes research that reflects the selectivity of high impact, innovative research you expect from the Science family of journals, published in an open access format to serve a vast and growing global audience. Check out the latest findings or learn how to submit your research: science.org/journal/sciadv

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CANCER

Naturally killing leukemia

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atural killer (NK) cells are innate immune cells that are under investigation as a cell therapy for multiple types of cancer. A challenge for NK cell–based therapies is ensuring that the cells persist and remain functional long-term. Berrien-Elliott et al. generated cytokine-induced memory-like NK (ML NK) cells as a therapeutic for leukemia and investigated their functional capacity and persistence in patients receiving human leukocyte antigen–haploidentical hematopoietic cell transplantation (HCT). The authors showed that ML NK cells derived from the same donor as the HCT persisted for at least 2 months after HCT and were highly functional ex vivo. Together, these findings support the use of ML NK cells as a component of HCT for leukemia. —CSM Sci. Transl. Med. 14, eabm1375 (2022). False-color scanning electron microscope image of a human natural killer cell

An exceptional laser cavity Laser cavities are typically simple structures in the sense that the pump light oscillates between the cavity walls symmetrically, ideally with a single resonant output mode. More complex cavity designs exploiting materials exhibiting gain and loss can be realized that result in an exceptional point at which the output mode can effectively be tuned. Schumer et al. designed a cavity in which the pump light encircles the exceptional point as it propagates back and forth within the cavity. The result is a laser capable of simultaneously emitting in two different, but topologically 832

linked, transverse profiles, each from a different facet of the cavity. The approach provides flexibility in designing topologically robust laser cavities. —ISO Science, abl6571, this issue p. 884

of semiconducting materials. The flakes attract each other through bond-free van der Waals interfaces to enable mechanical stretchability and malleability as well as permeability and breathability. These

NANOMATERIALS

Science, abl8941, this issue p. 852

Weaker interfaces enable conformal films Rigid materials become more flexible when cast as thin sheets, but they will still bump and buckle when subjected to in-plane rotation or twisting motions and thus cannot conformally cover a curved and mobile surface. Yan et al. formed roughly 10-nanometer-thick freestanding sheets by spin coating films containing flakes

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properties make them suitable for bioelectronic membranes that can monitor and amplify a range of electrophysiological signals, including demonstrations of electrocardiography and electroencephalography. —MSL

PROTEIN TARGETING

NAC acts as a gatekeeper on the ribosome

A flexible, wearable film containing semiconducting flakes is well suited for application to skin.

In eukaryotes, signal recognition particle (SRP) targets membrane and secretory proteins to the endoplasmic reticulum (ER) while they are being synthesized on the ribosome. To prevent erroneous targeting of proteins to the ER, access of SRP is science.org SCIENCE

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OPTICS

regulated by the nascent polypeptide–associated complex (NAC). Jomaa et al. investigated how NAC can prevent SRP from binding ribosomes that are synthesizing cytosolic and mitochondrial proteins while at the same time recruiting SRP to ribosomes translating an ER protein client. Their findings reveal the role of NAC as a key sorting factor for nascent chains that helps to ensure the specificity of membrane and secretory protein localization in eukaryotes. —SMH Science, abl6459, this issue p. 839

DARK MATTER

The search for axion dark matter The hypothetical “axion” particle is gaining momentum as a candidate for explaining the ever enigmatic “dark matter,” which is thought to account for about 85% of the matter in the universe. Chadha-Day et al. reviewed what this particle is, and Semertzidis and Youn reviewed how scientists are trying to detect it. Axion dark matter is proposed to consist of an oscillating radiofrequency field coupled to ordinary matter with charge-parity violating interactions. Detection experiments use magnetic fields to try to convert dark matter axions into weak signals of radiofrequency photons. New experimental typologies and advances in precision measurement have dramatically expanded the range of detectability, and hopes are high that they may succeed in discovering the axion in the near future. —MNA

PHOTO: HENK BOGAARD/ISTOCK.COM

Sci. Adv. 10.1126/sciadv.abj3618 (2022), 10.1126/sciadv.abm9928 (2022).

STRUCTURAL BIOLOGY

Movie of a moving chloride ion Biological pumps that use retinal isomerization to move protons across a membrane have been studied extensively, SCIENCE science.org

but the mechanisms involved in moving chloride ions, which have both a different charge and different coordination requirements, are less well understood. Mous et al. combined timeresolved x-ray crystallography, spectroscopy, and computational simulations to generate a molecular movie of chloride transport through a chloridepumping halorhodopsin. Ion uptake from the extracellular environment is supported by interactions with the retinal, and transport through a space generated by retinal isomerization occurs within about 1 microsecond of excitation. Release of chloride and blockage of backward flow is mediated by a salt bridge that forms an electrostatic gate at the intracellular face. These insights are important for understanding ion transport in these pumps, which are important tools for optogenetic silencing of neurons. —MAF

IN OTHER JOURNALS

Edited by Caroline Ash and Jesse Smith

NEUROSCIENCE

The elephant’s trunk

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n the trigeminal ganglion reside cell bodies of neurons that serve the face. For the elephant, this includes its trunk. Purkart et al. have made an anatomical analysis of the trigeminal system in Asian and African bush elephants. A trunk sensory neuron can be as much as 2 meters in length and is exuberantly supported by glial cells. The elephant’s trigeminal ganglion is larger in diameter than its spinal cord. The infraorbital nerve, which serves the trunk, is thicker than those serving the eye or inner ear. The authors suggest that the unusually thick axons in the trigeminal nerve support temporal precision, highlighting the trunk not only for its utility in manipulating the elephant’s environment but also for its contribution of sensory input for the elephant. —PJH Curr. Biol. 10.1016/j.cub.2021.12.051 (2022).

The sensory neuron of an elephant’s trunk is up to 2 meters in length to enable precise manipulation and sensitivity.

Science, abj6663, this issue p. 845

CANCER IMMUNOLOGY

Shared states of tumor-specific T cells Adoptive cell therapy is a type of cancer immunotherapy in which an individual’s immune system is trained to eliminate their tumor. This process involves genetically engineering T cells, but it requires the challenging identification of T cell receptors (TCRs) that can recognize cancer-specific alterations. Lowery and Krishna examined TCRs from human metastatic tumors, including those of breast, melanoma, and colon origin. Using TCR and singlecell sequencing technology, the authors found a conserved phenotypic state common to known tumor mutation–specific T cells. Gene signatures were able to predict the tumor reactivity of TCRs from independent samples and discriminate them from bystander T cells. Such strategies may enable more streamlined identification of tumor-specific TCRs for patient immunotherapy. —PNK Science, abl5447, this issue p. 877

PHYSIOLOGY

How exercise supports the brain How does exercise enhance neurogenesis in the adult hippocampus? The effect may in part result from increased amounts of the selenium transport protein selenoprotein P (SEPP1) in the

serum of exercised animals. Leiter et al. screened for proteins that increased in abundance in mice that exercised on a running wheel. One of them was SEPP1, which helps provide selenium to the brain. Genetic depletion of SEPP1 or its receptor reduced the effect of exercise on neural precursor cell proliferation. Dietary

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BEHAVIORAL GENETICS

Nature-loving inheritance

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hy some people spend more time outdoors could be explained by factors such as place of residence, parental influence, and childhood experience. Chang et al. found that genetics also plays a part in determining the strength of an individual’s desire to experience nature. Of 1100 pairs of twins in the TwinsUK panel, comparing those who were raised together with twins raised apart and nonidentical twins revealed that nature-loving behavior has a significant inheritable component. Like genes make like minds. —DJ PLOS Biol. 20, e3001500 (2022). Twins Tashi and Nungshi Malik, who have climbed Everest, likely share a genetic component in their love of the outdoors.

design, in which removing negatively charged residues drives aberrant association. The effect of alanine mutations in additional complexes indicates that such negative design is common. The resulting changes in protein assembly and localization could be important in both normal physiology and disease. —VV Proc. Natl. Acad. Sci. U.S.A. 119, e2101117119 (2022).

Cell Metab. 10.1016/ j.cmet.2022.01.005 (2022).

HYDROGELS BIOCHEMISTRY

Avoiding assembly by negative design Many diseases are caused by mutations that affect how proteins self-assemble or localize in cells, but mapping these relationships is challenging. Seisdedos et al. randomly mutated three residues at the surface of each of two homo-oligomeric complexes from Escherichia coli. In both cases, some mutants triggered nuclear localization and the formation of puncta or fibers. For one complex, this was driven by so-called positive design, changes that drive association by increasing surface hydrophobicity or stickiness. The other complex provides an example of negative 834

Swelling polymers with polymers Hydrogels consist of highly crosslinked polymers heavily swollen with water. These soft, squishy materials have thus found use in biomedical applications, but they are limited by their lack of toughness and the need to keep their water from evaporating over time. Wang et al. developed gels based on cross-linked poly(hydroxyethyl methacrylate–co–acrylic acid) polymerized in the presence of short polyethylene glycol chains. This combination results in gels with high stretchability and toughness and the ability for rapid self-healing and long-term stability under ambient conditions. This combination of properties make

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these gels suitable for pneumatically driven soft actuators useful for a robotic gripper. —MSL Adv. Mat. 10.1002/ adma.202107791 (2022).

reconsider career development advice provided to PhD candidates and postdocs. —MMc PLOS One 10.1371/ journal.pone.0263185 (2022).

SCIENTIFIC WORKFORCE

POROUS FRAMEWORKS

Not all postdocs are created equal

Alkane separations branch out

Using National Science Foundation data, Denton et al. shed light on employment implications for physical sciences and engineering (PSE) and life sciences (LS) postdocs in government, industry, and academia. The authors found that for each sector, PSE postdocs are shorter and offer higher salaries than LS postdocs. Further, transitioning from a postdoc to permanent employment occurred more frequently within sectors than between sectors, although a substantial number of academic postdocs transitioned to different sectors. Finally, the data showed that the least frequent reason for engaging in a postdoc was the lack of other options, refuting a common narrative that postdocs are a last resort for some. Collectively, these results provide data with which to

Microporous materials such as metal-organic frameworks (MOFs) can enable hydrocarbon isomer separations and have been used to separate linear from monobranched isomers. Yu et al. report that a ytrrium-based MOF containing two types of structure-building units is effective for separating three types of hexane isomers. The use of less-symmetrical 5,5′-azanediyldiisophthalic acid linkers enabled the coexistence of hexanuclear Y6(OH)8(COO)8 secondary building units and mononuclear Y(COO)4 primary building units and created a MOF with a new topology. The pores absorbed the more branched 2,2-dimethyl butane more readily than 3-methylpentane, which in turn was adsorbed preferentially compared with linear n-hexane. —PDS J. Am. Chem. Soc. 10.1021/ jacs.1c12068 (2022). science.org SCIENCE

PHOTO: VIRENDER SINGH MALIK/WIKIMEDIA COMMONS/CC BY-SA

supplementation of selenium mimicked the effect of exercise and reduced some of the cognitive defects brought on by aging. Understanding the mechanism of these effects might allow treatments that reproduce the exercise benefit. In the meantime, the authors note that selenium is found in foods such as nuts, dairy products, and grains. —LBR

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ALSO IN SCIENCE JOURNALS NEUROSCIENCE

Aging and sleep disruption In humans, the deterioration of sleep quality during aging is one of the most prevalent complaints. In an animal model, Li et al. found that aging correlated with enhanced spontaneous activity of wake-promoting brain areas during sleep (see the Perspective by Jacobson and Hoyer). Hypocretin-expressing neurons were more active during sleep, raising the chances of brief arousals and thus causing sleep to be more fragmented. The excitability of hypocretin neurons in aged brain tissue was heightened, possibly because of decreased expression of a subpopulation of potassium channels. Aging-related sleep fragmentation may therefore be due to altered intrinsic excitability of arousal-promoting neurons. —PRS Science, abh3021, this issue p. 838; see also abo1822, p. 816

IMMUNOLOGY

Trained ILC3: Better, faster, stronger! Type 3 innate lymphoid cells (ILC3s) are enriched in the intestinal tract and play important roles in mucosal homeostasis, host defense, and the organization of lymphoid tissues. Although certain innate immune cell populations can adopt new long-term phenotypes in response to inflammatory signals (“trained immunity”), whether this is also true of ILC3s is unclear. Serafini et al. report that after mice were infected with Citrobacter rodentium, a subset of activated ILC3s persisted for months. These “trained” ILC3s (Tr-ILC3s) showed superior activation and controlled infection better than “naïve” ILC3s after pathogen rechallenge. The initial encounter with C. rodentium durably rewired the metabolic pathways SCIENCE science.org

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of Tr-ILC3s, endowing them with an enhanced capacity to proliferate and secrete cytokines such as interleukin-22. —STS Science, aaz8777, this issue p. 859

activation by a light-absorbing sensitizer then tilts the equilibrium of enamine isomers to favor net conversion of a single aldehyde enantiomer into its counterpart. —JSY Science, abl4922, this issue p. 869

CORONAVIRUS

Ongoing adaptation of SARS-CoV-2 Two years into the COVID-19 pandemic, several variants of severe acute respiratory syndrome coronavirus 2 (SARSCoV-2) have arisen that show increased infectivity or evade immunity. The Omicron variant of concern has 37 mutations in the spike protein, which is responsible for host cell entry. Most of these mutations are in two domains targeted by neutralizing antibodies, the receptor-binding domain (RBD), and the N-terminal domain (NTD). McCallum et al. present structures of the viral spike bound to S309, a therapeutic antibody that maintains neutralizing activity against Omicron, and structures of the RBD bound to S309 and the human ACE2 receptor. The structures show how Omicron retains highaffinity binding to ACE2 while greatly reducing binding to other therapeutic antibodies. —VV

BLACK HOLES

Misaligned spin in an x-ray binary If a black hole is in a close enough binary system with a star, it rips material off the companion. As that material falls into the black hole, it forms an accretion disk that is hot enough to emit optical and x-ray radiation. Poutanen et al. used optical polarimetry to determine the orbital axis of a black hole x-ray binary (see the Perspective by Patat and Mapelli). Combining these observations with previous measurements of the black hole spin showed that the two are misaligned by at least 40 degrees. This high misalignment must have been generated during the formation of the black hole, because accretion always brings the two axes closer together. —KTS Science, abl4679, this issue p. 874; see also abn5290, p. 821

Science, abn8652, this issue p. 864

ANTIBIOTIC RESISTANCE ORGANIC CHEMISTRY

Twisting enamines through the mirror Separating enantiomers, or mirror-image molecules, is essential to pharmaceutical synthesis. Enriching an equal mixture of them by selectively converting one to the other is not possible using catalysis alone. Recently, however, an approach pairing catalysis with energy injection from light absorption has proven feasible. Huang et al. report a variant of this strategy whereby a chiral amine catalytically cycles chiral aldehydes through enamine derivatives. Selective

Personal histories of past resistance

by Lugagne and Dunlop). Data on antibiotic use for urinary tract and wound infections were used to train the algorithms and to develop personalized antibiotic treatment strategies. For most patients, there was an alternative susceptibility-matched antibiotic that had a lower predicted risk of resistance emerging compared with the antibiotic prescribed by the physician. —CA Science, abg9868, this issue p. 889; see also abn9969, p. 818

ORGANIC CHEMISTRY

A late coupling for himastatin Himastatin is a bacterial natural product that has been studied over the past several decades for its antibiotic properties and intriguing structure. The compound is a dimer of peptide macrocycles linked through a bond between the aryl rings of two cyclotryptophan residues. D’Angelo et al. report a comparatively efficient synthesis of himastatin as well as its unnatural enantiomer and several other derivatives (see the Perspective by Smith). The key step is a latestage dimerization relying on oxidation of the monomers by a copper salt. Fluorescent tagging sheds light on the compound’s cell membrane–disrupting mechanism of action. —JSY Science, abm6509, this issue p. 894; see also abn8327, p. 820

A serious infection may initially be diagnosed as antibiotic susceptible but subsequently become drug resistant—and life threatening. Rather than de novo resistance mutation occurring, it is more likely that a resistant strain or species persisting in the patient’s gut or skin replaces the susceptible strain. From this starting point, Stracy et al. built machine-learning models that predict individual risks of gaining resistance to specific antibiotics using 8 years of records on more than 200,000 patients’ microbiome profiles (see the Perspective

INTERFERON SIGNALING

From bone marrow to hemorrhage Hemorrhaging is a potentially fatal outcome of arenaviral infections and is related to increased interferon-a (IFN-a) production. Aiolfi et al. found that bleeding from arenaviral infection in mice resulted from IFN-a triggering the formation of defective platelets through a pathway that did not act directly on platelets, which lack IFN receptors.

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Instead, IFN-a decreased the expression of genes involved in platelet formation and function in megakaryocytes, the bone marrow cells that generate platelets. Infected mice produced fewer platelets, and those that were produced were less functional. —WW

expanded roles and versatility in three-dimensional OLHPs, especially for structural stabilization, mitigation of ion migration, and surface functionalization for interface modification and trap passivation. —PDS

of scintillation. This approach should enable the development of brighter, faster, and higherresolution scintillators. —ISO Science, abm9293, this issue p. 836; see also abn8478, p. 822

Science, abj1186, this issue p. 835

Sci. Signal. 15, eabb0384 (2022).

HUMAN EVOLUTION ALLERGY

Stress leads to IL-9 danger Interleukin-9 (IL-9) can promote type 2 lung inflammation during allergic responses to inhaled allergens, but the direct cellular targets of IL-9 are not well characterized. Fu et al. showed that pulmonary macrophages are a major population of immune cells responding to IL-9 produced in mouse models of allergic airway disease. Mice deficient in the IL-9 receptor had impaired expansion of monocyte-derived interstitial macrophages that promoted airway inflammation dependent on arginase expression. IL-9 signaling also promoted macrophage production of the eosinophil-attracting chemokine CCL5, which was elevated in the serum of patients with asthma and correlated with IL-9 levels. These results identify lung macrophages as key cellular targets of IL-9 during allergic disease that subsequently amplify type 2 inflammatory responses. —CO Sci. Immunol. 7, eabi9768 (2022).

SOLAR CELLS

Optimizing perovskite A sites In the organic-inorganic lead halide perovskites (OLHPs) used in optoelectronics, the monovalent A site was thought initially to have little effect on band edge states compared with the divalent lead or tin cations and halide anions. However, the recent improvement performance breakthroughs for OLHP solar cells have largely come from modifications of A site cations. Lee et al. reviewed their 834-C

Genomics and human ancestral genealogy Hundreds of thousands of modern human genomes and thousands of ancient human genomes have been generated to date. However, different methods and data quality can make comparisons among them difficult. Furthermore, every human genome contains segments from ancestries of varying ages. Wohns et al. applied a tree recording method to ancient and modern human genomes to generate a unified human genealogy (see the Perspective by Rees and Andrés). This method allows for missing and erroneous data and uses ancient genomes to calibrate genomic coalescent times. This permits us to determine how our genomes have changed over time and between populations, informing upon the evolution of our species. —LMZ Science, abi8264, this issue p. 836; see also abo0498, p. 817

NANOPHOTONICS

Scintillating nanophotonics When a high-energy particle collides with a material, the energy is transferred to atoms in the material, and light can be emitted. This scintillation process is used in many detector applications ranging from medical imaging to high-energy particle physics. Roques-Carmes et al. integrated scintillating materials with nanophotonic structures to enhance and control their light emission (see the Perspective by Yu and Fan). The authors show how nanophotonic structures enable the ability to shape the spectral, angular, and polarization characteristics

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Rethinking the A cation in halide perovskites Jin-Wook Lee†, Shaun Tan†, Sang Il Seok*, Yang Yang*, Nam-Gyu Park*

BACKGROUND: Organic-inorganic lead halide

perovskites (OLHPs) represent a family of semiconducting materials that have attracted wide interest for their optoelectronic applications. By combining notable electronic and photophysical properties with low-temperature solution processability using earth-abundant materials, the field has experienced rapid breakthroughs over the past decade. OLHPbased optoelectronic devices have now been established as an independent field of study. In particular, solar cells that use OLHPs as the photoactive layer have exceeded 25% power conversion efficiency, which is competitive with photovoltaics based on traditional inorganic semiconductors such as silicon. However, unanswered questions remain to be addressed regarding the fundamental properties and our understanding of OLHP materials. ADVANCES: OLHPs have the general chemical

formula of ABX3, where A represents a monovalent cation, B represents the divalent lead cation, and X is a halide anion. During its initial development, the A cation was limited to mainly three candidates, namely methylam-

monium (MA+), formamidinium (FA+), and cesium (Cs+), which were determined by size and structural constraints to fit within the spaces of the OLHP crystal lattice. Because the A cation, by itself, does not directly contribute to the OLHP band-edge construction, it was traditionally believed to hardly affect the optoelectronic properties of OLHPs. In contrast to these presumptions, advancements in recent years have unraveled the critical role of the A cation in determining the optoelectronic and physicochemical properties of OLHPs. Major breakthroughs in the field have been realized by using A cations to fine-tune the properties of OLHPs, including for (i) thermodynamic or kinetic stabilization of desirable OLHP phases, especially the metastable cubic formamidinium lead triiodide polymorph; (ii) impeding the migration of ions by electrostatic interactions and/or steric effects; and (iii) surface and interface functionalization and modification. These topics are now at the forefront of OLHP research, ultimately dictating the utility, function, performance, and stability of OLHP-based optoelectronic devices.

In this review, we examine the important developments enabled by the expanded role of the A cation. To highlight its importance, the vast majority of the record-breaking performances for OLHP-based photovoltaics have been enabled by breakthroughs related to the versatility of the A cation, which we discuss. Moreover, recently, bulky conjugated A cations have even been demonstrated to participate in constructing the OLHP band-edge structure, further challenging a long-held traditional notion regarding the role of the A cation. OUTLOOK: Future opportunities entail either

discovering new uses for existing A cation species or identifying new A cations for existing applications, or both simultaneously. When looking toward improving the commercialization readiness of OLHPs, A cation applications that involve addressing the module scale-up challenges and long-term operational instability issues must be further explored. This necessitates a more comprehensive understanding of the structure-property-performance-stability correlations conferred by the A cation by combining systematic experimental approaches with first-principles theoretical studies.

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The list of author affiliations is available in the full article online. *Corresponding author. Email: [email protected] (S.I.S.); [email protected] (Y.Y.); [email protected] (N.-G.P.) These authors contributed equally to this work. Cite this article as J.-W. Lee et al., Science 375, eabj1186 (2022). DOI: 10.1126/science.abj1186

READ THE FULL ARTICLE AT https://doi.org/10.1126/science.abj1186

Modifying perovskites through A site cations. In recent years, important breakthroughs have been enabled by the expanded role and function of the A cation in tailoring the physicochemical and optoelectronic properties of OLHPs. These advances ultimately dictate the utility, function, and performance of OLHP-based optoelectronic devices. SCIENCE science.org

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Rethinking the A cation in halide perovskites Jin-Wook Lee1†, Shaun Tan2,3†, Sang Il Seok4*, Yang Yang2,3*, Nam-Gyu Park5* The A cation in ABX3 organic-inorganic lead halide perovskites (OLHPs) was conventionally believed to hardly affect their optoelectronic properties. However, more recent developments have unraveled the critical role of the A cation in the regulation of the physicochemical and optoelectronic properties of OLHPs. We review the important breakthroughs enabled by the versatility of the A cation and highlight potential opportunities and unanswered questions related to the A cation in OLHPs.

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rganic-inorganic lead halide perovskites (OLHPs) have the general stoichiometry formula of ABX3, with A as the monovalent organic or inorganic cation, B as the divalent Pb2+ cation, and X as the halide anion. Any of the A, B, and X sites can be occupied by a mixture of constituents to afford OLHPs a wide compositional breadth and tuneability toward different applications (1, 2). The Goldschmidt tolerance factor can be useful to predict structural formability and the resulting crystal phase based on ionic size considerations; it is defined by rA þ rX t ¼ pffiffiffi 2ðrB þ rX Þ where rA, rB, and rX are the ionic radii of the A, B, and X species, respectively. The perovskite phase is desired for many practical optoelectronic applications and empirically observed to form at 0.8 < t < 1.0. The crystal structure consists of an inorganic BX64– octahedra network that is three-dimensionally connected through the corner halides, with structural stabilization contributed by the A cations that occupy the cuboctahedral spaces surrounded by eight BX64– octahedra. For APbI3-based stoichiometries, three A cations are known to definitively fit this geometric constraint, namely methylammonium (CH 3NH 3+ , or MA+), formamidinium [HC(NH2)2+, or FA+], and cesium (Cs + ), albeit FAPbI 3 (t ~ 0.99) and CsPbI3 (t ~ 0.80) are at the edges of the t limits. 1

SKKU Advanced Institute of Nanotechnology (SAINT) and Department of Nanoengineering, Sungkyunkwan University, Suwon 16419, Republic of Korea. 2Department of Materials Science and Engineering, University of California, Los Angeles, CA 90095, USA. 3California NanoSystems Institute, University of California, Los Angeles, CA 90095, USA. 4Department of Energy Engineering, School of Energy and Chemical Engineering, Ulsan National Institute of Science and Technology, Ulsan 44919, Republic of Korea. 5 School of Chemical Engineering and Center for Antibonding Regulated Crystals, Sungkyunkwan University, Suwon 16419, Republic of Korea. *Corresponding author. Email: [email protected] (S.I.S.); [email protected] (Y.Y.); [email protected] (N.-G.P.) These authors contributed equally to this work.

Lee et al., Science 375, eabj1186 (2022)

Traditionally, the A cation was not believed to directly contribute to the OLHP band-edge construction, which is primarily composed of orbital states from the B and X species (3). Resultantly, the A cation was not thought to substantially affect the optoelectronic properties of OLHPs. However, progress in recent years has since challenged this notion. Furthermore, the A cation has been shown to critically influence the physiochemical properties and the intrinsic and extrinsic stability of OLHPs. In this review, we evaluate the expanded role of the A cation (Fig. 1), which has enabled many important breakthroughs for highperformance and stable OLHP optoelectronics. Many of these developments were made possible by the introduction of oversized (t > 1) or undersized (t < 0.8) cations that may not necessarily fit the structural constraints of the lattice bulk. Conversely, such missized cations may occupy the A sites along the surfaces and/ or grain boundaries, which are free from the bulk steric constraints. By themselves, the oversized cations typically form lower-dimensional phases, such as the two-dimensional (2D) A2PbI4 perovskites, whereas the undersized cations are used to form the ABO3 oxide perovskite structures. We focus only on their utility to and function in tuning the properties of three-dimensional (3D) OLHPs. Revisiting the conventional roles of the A cation: Progress and challenges Crystal symmetries and crystal phases

The size and geometry of the A cation affect the bond length and angle between the B and X species to alter the arrangement of the surrounding BX64– octahedra and thus the resulting crystal symmetry and phase of the perovskite. The molecular orbitals of the A cation constitute deep energy states within the conduction and valence bands and thus do not directly affect the band-edge carrier properties (4). Consequently, A cation engineering has been considered as a useful approach to fine-tune the crystal structure (orthorhombic, tetragonal, and cubic) and

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physicochemical properties of OLHPs without substantially altering their optoelectronic properties. The organic A cations interact with the surrounding BX64– octahedra through weak secondary hydrogen bonding, with bonding energies lower than 0.1 eV per bond (5). Owing to such weak interaction energies, the reorientation of the organic cation can be thermally activated at a finite temperature. [The residence time at room temperature is on the order of ~102 femtoseconds to picoseconds (6–8).] The activated reorientation of the organic A cation and its coupling with the surrounding inorganic framework result in a temperaturedependent order-disorder–type phase transition between the orthorhombic, tetragonal, and cubic phases (9, 10). For example, MAPbBr3 crystallizes in the orthorhombic phase at low temperatures ( 1) ammonium cations are another class of wide-bandgap OLHPs that have been broadly explored (26). The bulky insulating ammonium cations that are intercalated between the 3D OLHP layers induce charge-carrier quantum confinement to enable bandgap engineering by varying the number of

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Charge-carrier dynamics

Although band-edge carrier transport is mediated through the BX64– network, the thermally activated reorientational motion of dipolar A cations and coupled BX64– octahedra may interact with charge carriers to affect their dynamics (7). It was suggested that the formation of (ferroelectric) large polarons, that is, charge carriers dressed by long-range lattice deformations (Fig. 2C), may be the possible origin of the long carrier lifetimes of OLHPs (29, 30). The hot-carrier lifetime in OLHPs was found to be ~102 ps, which is exceptionally long compared with the ~102 fs lifetime of conventional polar semiconductors (7, 31). This further suggests the potential application of OLHPs to hot-carrier solar cells, which remain relatively unexplored. It was proposed that the ultrafast reorientational motion of the A cation in response to the photogeneration of charge carriers may form large polarons, resulting in an effective screening of the Coulomb potential to diminish hot-carrier scattering (7). The long-lived hot carriers are observed in MAPbBr3 and FAPbBr3, but not CsPbBr3. However, separate studies show an opposite trend, where the slower hot-carrier cooling of CsPbBr3 is attributed to a relatively weak charge carrier– phonon coupling compared with its hybrid counterparts (32). Nevertheless, these studies highlight the importance of the dynamic motion of the A cation. The role of the A cation in the band-edge carrier dynamics is still under debate. In contrast to initial reports correlating polaronic stabilization with A cations (7), recent consensus seems to be that the generation of large polarons is more closely associated with the dipolar BX6 4– sublattice rather than the A cation, which is supported by the similar radiative recombination kinetics of band-edge carriers in MAPbBr3, FAPbBr3, and CsPbBr3 (33). Conversely, experimental observations still indicate that the lifetimes of band-edge carriers are greatly affected by the A cation composition. For example, FAPbI3-based compositions have demonstrated much longer charge-carrier lifetimes compared with that of MAPbI3, irrespective of the former’s generally inferior crystallinity and poor phase purity (34, 35). Based on solid-state nuclear magnetic resonance (NMR) investigations, there exists a correlation between the faster reorientation 2 of 10

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Therefore, further studies are required to unravel the correlations between the A cation and charge-carrier dynamics, which are essential for designing OLHP compositions. Expanded role of the A cation Phase stabilization of desired perovskite polymorphs

Fig. 2. Revisiting the conventional roles of the A cation. (A) Schematics illustrating the dynamic motion of the MA+ cation (left) and temperature-dependent order-disorder–type phase transition of MAPbBr3 induced by the MA+ cation motion (right). Adapted with permission from (6) and (11). Labels (1) and (2) on the left figure indicate the two reorientation modes: (1) methyl and/or ammonium rotation around the C–N axis (carbon and nitrogen atoms are depicted in blue and brown, respectively, and the axis is indicated by the green dotted lines); and (2) whole-molecule reorientation via rotation of the C–N axis itself. (B) Low-dimensional PEA2MAn–1PbnI3n+1 perovskites and their corresponding relative formation energy and stability. Adapted with permissions from (27). (C) Schematic of the ferroelectric large polarons and molecular dynamics simulation of the corresponding isodensity representation of holes, showing sheet-like charge localization in tetragonal MAPbI3. Adapted with permission from (29). (D) History of the record PSC performance and the A cation compositions that were used. The PCE data and compositions are retrieved from their respective publications (1, 2, 19, 45, 49–51, 87, 102–110). The PCEs are plotted based on publication date. This panel conveniently summarizes the composition evolution of state-of-the-art PSCs with time, but we note that the final PSC efficiency is not solely determined by composition alone.

dynamics of the A cation and longer chargecarrier lifetimes (36). The temperature and resulting phase-dependent charge-carrier lifetime have also been correlated with the rotational entropy of the A cation (37). Recent computational studies proposed that charge carriers are weakly localized by the fluctuating organic A cation, although the subsequent energetic stabilization to form polarons is mediated by Lee et al., Science 375, eabj1186 (2022)

the BX64– sublattice (38). It was also suggested that polaron hopping is related to the random reorientation of the organic cations. This again implies that the dynamic structure of the organic A cation plays a crucial role in affecting OLHP optoelectronic properties. However, all the observed carrier dynamics could have also manifested from compositiondependent defect type, density, and energetics.

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More recent record-breaking PSCs contain continuously increasing proportions of FA+ in their compositions (Fig. 2D). Compared with the prototypical MAPbI3, FAPbI3-dominant compositions generally boast longer carrier lifetimes, superior thermal and photostability, and a bandgap closer to the ideal for photovoltaic applications (3). Stabilization of the metastable cubic FAPbI3 phase at room temperature has become an important focus of ongoing research in the community (Fig. 3A). Initially, substitution with the smaller MA+ cation was widely used to lower the t value of FAPbI3. Replacement of FAI with MAI or MABr in the precursor solution contributes to cubic phase stabilization at room temperature (19, 39). The (FAPbI3)1–x(MAPbI3)x or (FAPbI3)1–x(MAPbBr3)x compositions demonstrated superior optoelectronic properties and stability compared with pure MAPbI3 or FAPbI3, resulting in several record-breaking certified efficiencies around 2015 (Fig. 2D) (3). However, MA+ forms a smaller number of hydrogen bonds than FA+ with the surrounding PbI64– inorganic framework, and its consequent volatile nature aggravates the thermal and photo instability of the OLHP films (40, 41). This motivated the development of alternative cations to stabilize the cubic polymorph. The inorganic Cs+ and Rb+ cations have a smaller ionic radius than FA+ but form stronger primary chemical bonding with the BX64– framework. Consequently, Cs+ and Rb+ effectively stabilize the cubic phase at lower temperatures while simultaneously enhancing the environmental stability of the films (41–43). It was also suggested that A cation mixing contributes entropic stabilization to the system (44), which motivated the development of more complex triple or quadruple cation systems such as FA1–x–yMAxCsy- or FA1–x–y–zMAxCsyRbzbased compositions (45, 46). Regardless of the improved phase stability of most FAPbI3based compositions by substitution with MA+, Br–, or Cs+, however, these approaches inevitably increase the bandgap to sacrifice the photocurrent. Recently, the focus of the community has shifted to phase-stabilization strategies that can preserve the inherent bandgap of cubic FAPbI3. To minimize the bandgap penalty, “additive removal” approaches have been developed by using the smaller MA+ cation to first form a highly crystalline perovskite phase and then removing it afterward. MACl is, at present, the most widely used additive among 3 of 10

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Fig. 3. Stabilization of the cubic FAPbI3 phase by A cation engineering. (A) Schematics illustrating the metastability of the cubic a-FAPbI3 phase and its corresponding free-energy diagram (left) and approaches to stabilize the cubic a-FAPbI3 phase by tuning the bulk or surface free energy (right). R.T., room temperature. (B) Schematic illustration of lattice strain engineering by using MDA2+ and Cs+ cations. Adapted with permission from (51). (C) Schematics showing the free-energy diagrams at different temperatures and refined structures of FAPbI3 at the corresponding temperatures. At temperatures lower than the phase-transition temperature (Tc), the FA+ cation is oriented within the hexagonal crystal structure, whereas its orientation becomes isotropic (random) in the cubic crystal structure at temperatures higher than Tc, contributing to the entropy of the system. Adapted with permission from (12).

these approaches (47, 48). The MA+ cation from the added MACl initially participates in forming the perovskite intermediate phase at room temperature. During the subsequent annealing process, the intermediate phase is converted into the perovskite crystals with the vaporization of MACl. The slow vaporization of MACl and thus retarded crystal growth kinetics promote the growth of highly crystalline perovskite crystals. Regardless of the high molar concentrations of the excess MACl (~40 mol %) in the precursor solution, the final OLHP films contain only a small amount of residual MA+ (~5 mol %) (49), and thus their bandgaps (~1.50 to 1.53 eV) are comparable to that of pure FAPbI3. This approach enables the formation of phase-pure and highly crystalline FAPbI3-based films, and it has been broadly used in studies that report record-efficiency PSCs (vertical dashed line in Fig. 2D) (50, 51). Lee et al., Science 375, eabj1186 (2022)

Relatedly, the dual combination of MACl and CsCl was also found to effectively stabilize the perovskite phase (52). A similar approach was developed by using gaseous methylammonium thiocyanate (MASCN) (53). It was reported that MASCN is incorporated onto the surface of hexagonal FAPbI3 crystals to assist in the conversion of the hexagonal phase into the cubic polymorph. For either MACl or MASCN, the counter anions were also reported to contribute to stabilizing the FAPbI3 perovskite phase. Further developments may elucidate the different roles of the counter anions as well as explore alternative cations or counter anions that can impart additional functionalities. The phase energetics of materials is governed by the Gibbs free energy of the phase, which is in turn determined by the summation of the bulk and surface free energies. Therefore, the phase conversion of metastable

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OLHP phases can be modulated by surfaceenergy manipulation. For example, it was demonstrated that the metastable CsPbI3 perovskite phase can be stabilized by synthesizing nanosized crystals where the surface-energy contribution becomes dominant compared with that of its bulk counterpart (54). Such an approach was found to be also valid for FAPbI3, where nanocrystalline FAPbI3 demonstrated a superior phase stability compared with its corresponding bulk crystals (55). Surface-energy modulation can also be achieved by adopting surface-functionalizing oversized A cations (56–58). Bulky ammonium cations, such as phenethylammonium (PEA+), butylammonium (BA+), or isopropylammonium, are spontaneously expelled to the grain boundaries and surfaces during perovskite crystallization because of their inability to incorporate into the crystalline lattice bulk. The bulky cations are free from steric constraints at the surface and thus can coordinate with the surface A site by bonding with the surface BX64–. Such surface functionalization was suggested to modulate the crystal surface energy to stabilize the cubic perovskite phase. This approach allows for the stabilization of metastable OLHP phases without changing its bulk composition and inherent bandgap. The phase energetics of OLHPs were also suggested to be dependent on the hydrogenbond number and bond strength between the A cation and surrounding inorganic framework (5). This is illustrated by using the divalent methylenediammonium (MDA2+) cation that can form a greater number of hydrogen bonds with the BX64– lattice than FA+ (50). Compared with MA+, lower concentrations of MDA2+ are required to stabilize the cubic phase of FAPbI3, even though the ionic radius of MDA2+ is slightly oversized compared with that of FA+. The incorporation of MDACl2 may generate FA vacancy and interstitial Cl defects to maintain charge neutrality but, importantly, without forming deep trap states. It is noteworthy that the PSC performance and stability improved regardless of the generated additional defects, but further investigations may be necessary to decouple their full consequences. Nevertheless, incorporation of MDA2+ inadvertently induces tensile lattice strain as a result of its large cation radius. A direct correlation between residual lattice strain and a detrimental effect on the OLHP charge carrier dynamics has been reported (59). To compensate for the residual strain, it was further reported that the smaller Cs+ cation can be incorporated in equimolar amounts with MDA2+ (Fig. 3B) (51). Tensile strain relaxation by Cs+ incorporation resultingly increased the carrier lifetime owing to a reduced defect concentration in the film. The case of MDA2+ illustrates the possibility of expanding into higher-valency cations for use in OLHPs, although 4 of 10

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their exact phase-stabilization mechanisms still need to be explored. More generally, the vast majority of FAPbI3 stabilization strategies now reported could be considered kinetic stabilization approaches, such that the cubic FAPbI3 phase only remains metastable and still spontaneously degrades into the equilibrium hexagonal phase. Although kinetic stabilization is effective in retarding phase degradation, true thermodynamic stabilization of cubic FAPbI3 as the equilibrium phase remains the elusive goal. To achieve this, understanding the many overlapping factors that affect the thermodynamic energetic landscape of OLHPs is required. For example, the thermally activated random motion of the FA+ cation and its entropic contribution to the phase energetics were found to have a crucial role in stabilizing the cubic phase (Fig. 3C) (12, 60), but the entropic contribution of the different A cations has barely been explored. Also, the effects of strain on OLHP thermodynamics and energetics have not been fully elucidated and require further systematic investigations. Defect states must also be correlated with the thermodynamic energetics of metastable OLHPs, which has been shown to affect the phase degradation of FAPbI3 (61). Impeding ion migration by steric and electrostatic interactions

The charged ionic constituents of OLHPs are mobile under an electric field and accelerated under illumination or at increased temperatures. An ion displaced from its original lattice site becomes a crystal defect (or Schottky, Frenkel defect pairs). Ion (or defect) migration are known to cause the current-voltage hysteresis, phase segregation, and chemical corrosion of reactive functional layers, which are responsible for PSC degradation during operation. Strategies to inhibit ion migration can be broadly categorized as reducing the density of mobile ions and/or increasing the activation energy barrier (Ea) for ions to migrate. Relative to single-cation compositions, substitutional doping to create mixed-cation compositions is broadly observed to alleviate PSC hysteresis. In mixed-cation compositions, the local lattice mismatch caused by A cations with different sizes was reported to distort the ionmigration pathways (Fig. 4, A and B) (62). This steric impediment effect was shown to increase Ea to suppress ion migration, which consequently improved the thermal and photostabilities of PSCs. Conversely, excessive lattice strain may detrimentally lower Ea, because ion redistribution constitutes a driving force to relieve residual strain (51, 63). This is especially relevant for pure CsPbI 3 and FAPbI3 owing to their extreme t values. The intrinsic strain in FAPbI3 was also shown to promote the formation of Schottky vacancy defects Lee et al., Science 375, eabj1186 (2022)

Fig. 4. Impeding ion migration. (A) Summary of reported Ea enhancements by A cation engineering, including the measurement and calculation methodologies. (AZ, azetidinium; BDA, 1,4-butanediamonium; OAm, oleylaminium). The PCE data and compositions are retrieved from their respective publications (57, 60, 62, 111Ð113). (B) Theoretically simulated iodide migration pathway for single-cation (top row) or mixed-cation (bottom row) compositions. The simulations were performed using the nudged elastic band and constrained energy minimization methodology. Adapted with permission from (62). (C) X-ray fluorescence mapping of the halide distribution of various mixed-halide perovskite films with different A cation compositions. Scale bars indicate 2 mm. Adapted with permission from (65). Ref, reference; FAMA, mixture of 8.3% FAI and 1.7% MAI. (D) Schematic illustrating the suppressed ion migration by grain boundary 2D (PEA)2PbI4. Adapted with permission from (77).

as a compensating strain relaxation mechanism (64). As a solution, partially substituting FA+ in FAPbI3 with smaller Cs+ and/or MA+ relaxes the intrinsic strain to suppress ion migration and defect formation (41, 51). Such strain relaxation using Cs+ has also been widely adopted to prevent phase segregation for wide-bandgap mixed-halide compositions (Fig. 4C) (65). Substitutional doping can also increase Ea by strengthening the structural integrity of the OLHP lattice. This is achieved by increasing the bond number and/or decreasing the bond length between the A cation and the BX64– framework. This is illustrated by partial substitution of guanidinium (GA+) into MAPbI3, where GA+ forms a greater number of effective hydrogen bonds than MA + (GA+, seven bonds; MA+, three bonds) with the

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PbI64– lattice (62, 66). Molecular dynamics simulations have further indicated that ion migration is affected by the A cation polarity (67). The study suggests that more-polar A cations (e.g., MA+ is more polar than FA+ ) may detrimentally assist halide migration because of a reorientation and charge-screening mechanism. The undersized alkali cations, focusing on Rb+ and K+, are widely used as additive dopants to reduce ion migration. The strongly electropositive cations can bind and immobilize excess and undercoordinated halides to suppress their unwanted migration (68). Theoretical simulations also indicate that alkali cation doping increases the formation energy of mobile halide interstitial defects (69). Additionally, assuming incorporation into the A 5 of 10

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site, the resultant lattice contraction decreases the ionic interaction distances to improve the structural integrity of the OLHP lattice (43, 46). There is ongoing debate regarding the residing location of the undersized cations, especially for Rb+. Experimental observations have been interpreted as incorporation into the lattice A site (43, 46). Based on t values, their ionic radii should be too small to fit into the A site of the APbI3 lattice. Theoretical calculations suggest that interstitial site occupation is energetically favorable (70–72). Conversely, solidstate NMR results suggest that Rb+ and K+ are entirely immiscible (even at the interstitial sites) and segregate into secondary photoinactive phases (73). These discrepancies may perhaps be related to varying miscibility limits of different OLHP compositions. For example, K+ incorporation may be facilitated by Br– in mixed-halide APbI3−xBrx stoichiometries (74). Particularly, if assuming the undersized cations are indeed expelled from the A site, alternative mechanisms that do not involve lattice occupancy must be elucidated to explain their ion-migration impediment effects. For example, interstitial site occupancy has been suggested to prevent lattice iodine from displacing into the filled interstitial sites, which inhibits the formation of mobile iodide Frenkel defects (iodine interstitial-vacancy pairs) (70, 75). Oversized organic A cations are often used as additive dopants into the precursor solution. As discussed, the bulky cations segregate at the grain boundaries and surfaces, possibly forming lower-dimensional phases depending on the specific species. The bulky cations can act as physical barriers to increase Ea by blocking the low-energy ion-migration channels through the grain boundaries (Fig. 4D) (76, 77). The –NH3+ functional group of ammoniumbased cations can also bind with negatively charged defects (e.g., A cation vacancies, undercoordinated halides) by electrostatic interactions to inhibit their migration and deactivate their charge-trapping ability. In an alternate perspective, the replacement of defective grainboundary regions with lower-dimensional phases equivalently decreases the overall defect density, thus reducing the overall concentration of mobile defective species. Functional groups can be introduced to the A cation chain to strengthen the bonding interaction between adjacent cations along the grain boundary to improve structural rigidity. This is exemplified by incorporating a carboxyl tail into BA+, forming 5-ammoniumvaleric acid (5-AVA). Adjacent 5-AVA cations interact through stronger hydrogen bonding rather than the van der Waals interaction between BA+ cations. Resultantly, doping of 5-AVA into MAPbI3 was reported to dramatically suppress the loss of MAI by ion migration–driven volatilization (78). Despite using the supposedly unstable MAPbI3 base Lee et al., Science 375, eabj1186 (2022)

composition, carbon-based 10-cm–by–10-cm solar modules doped with AVA+ were shown to sustain their performance for more than 10,000 hours under continuous illumination at 55°C (79). Bulky cyclic cation additives, including 1-butyl-1-methylpiperidinium (BMP) and 1-butyl-3-methylimidazolium (BMIM), have been reported to dramatically inhibit ion migration and OLHP decomposition even at increased temperatures (80, 81). It was proposed that BMP may simultaneously reduce the density of mobile iodide Frenkel defects and inhibit the migration of iodine interstitial defects, which quenched the formation rate of harmful I2 that catalyzes perovskite degradation (81). Ion migration–facilitated formations of d-FAPbI3 and segregated FAPbBr3 impurity phases during degradation may also be suppressed by BMP addition (81). Interestingly, BMIM was observed to aggregate predominantly at the buried interface, whereas BMP was distributed along the grain boundaries. It was suggested that the segregation of BMIM modified its interface dynamics to become incompatible with poly-TPD [poly(N,N′-bis4-butylphenyl-N,N′-bisphenyl)benzidine] as the bottom transport layer, whereas BMP addition was not affected by this problem. This comparison highlights the fact that additive doping can possibly incur unintentional side effects to negatively alter the perovskite crystallization dynamics or interfacial energy alignments. More generally, this emphasizes the importance of locating the distribution of different additive dopants within and around the OLHP layer. Ion migration is fundamentally a defectdriven process. Theoretical studies show that halide migration, mediated by vacancy defects, is the lowest-energy transport mechanism, with an Ea between 0.1 and 0.6 eV (82). However, the vast majority of mitigation strategies in the literature fall short of pinpointing the specific defect species that are immobilized or suppressed. Further studies are necessary to investigate the binding and interaction of A cations with the complex defect landscape of OLHPs to mechanistically explain their ion-migration impediment effects. Surface functionalization and interfacial modification

The OLHP surface is typically BX2-rich owing to a combination of volatilization of organic FA+ or MA+ during thermal annealing, dissolution of FA+ or MA+ by the deposition of solvent during surface posttreatment, or excess BX2, particularly excess PbI2, intentionally added to the precursor solution (83–85). Degradation initiation and nonradiative recombination losses predominantly occur at the OLHP top surface region as a result of an

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abundance of defective states (61, 86). Consequently, surface modification by posttreatments using A cations has become an essential processing step for state-of-the-art PSCs in recent years (Fig. 5, A and B). Unlike additive doping into the precursor solution that was discussed previously, surface treatments do not interfere with the initial perovskite crystallization process, which enables a larger variety of candidate cations to be used. An additional secondary annealing step typically follows deposition, which may facilitate a chemical reaction with BX 2 to form thin lower-dimensional phases at the surface. The deposition of PEA+ is a notable exception that omits the secondary annealing step. Formation of the 2D (PEA)2PbI4 was indeed observed to weaken the trap passivation effect (87). This distinction for different A cations, of whether formation of the lower-dimensional crystalline phase is preferred, is still not fully understood. Surface functionalization of A cations often confers beneficial trap passivation and environmental protection effects. For the former, various functional groups on the cation can coordinate with surface defects to passivate their charge-trapping ability. Most commonly, the –NH3+ group of ubiquitous ammonium-based cations interacts with negatively charged defects (85). Chemical and structural tailoring of the cation backbone is often used to enhance its binding and interaction with surface traps. This is illustrated by the incorporation of the tert-butyl moiety (25, 88), which also has the additional benefit of improving the interfacial contact with spiro‐ MeOTAD [2,2′,7,7′-tetrakis(4,4′-dimethoxy-3methyldiphenylamino)-9,9′-spirobifluorene] to facilitate hole extraction (88). Conversely, the –NH3+ functionality is insensitive to positively charged defects, such as halide vacancies, which readily form at the OLHP surface. This can be remedied by using zwitterions to simultaneously coordinate with both oppositely charged defects, for instance, by incorporating carboxyl or phosphate groups into the ammonium chain (25, 89). Regarding environmental protection, bulky A cations with hydrophobic chains that orient out of plane with the surface can repel H2O and O2 ingression while simultaneously limiting the escape of the OLHP constituents from the active layer. Well-known hydrophobic groups include tertiary or quaternary hydrocarbons (e.g., tetra-ethylammonium) (88–90) and/or electron-withdrawing fluorine moieties, such as in 4-fluorophenylethylammonium or pentafluorophenylethylammonium (60, 91). In general, a large variety of useful backbone-chain modifications can be found in the literature to enhance such desirable effects. However, despite these successes, concrete selection and design rules still need to be established to avoid 6 of 10

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Fig. 5. Surface and interface modification by oversized A cations. (A) Summary of state-of-the-art PSCs with certified performance since 2019, highlighting the surface functionalization by the oversized A cations that were used. The data are plotted based on publication date. NREL, National Renewable Energy Laboratory. (B) Corresponding photovoltaic parameters from (A), with the horizontal dashed lines marking the theoretical Shockley-Queisser limits of each parameter for a bandgap of 1.5 eV. JSC, short-circuit current; VOC, open-circuit voltage; FF, fill factor. (C) Schematic of the surface-induced secondary grain growth (SISG) process by using alkylammonium functionalization to control the surface-energy anisotropy (left). Top-view scanning electron microscopy images of the perovskite films treated with various alkylammonium cations of different chain lengths (right). Adapted with permission from (93). g, surface energy; OCA, octylammonium; OLA, oleylammonium. (D) Schematic illustrating the interactions of different pyrene-based ammonium cations with the OLHP film surface (left). Ultraviolet photoelectron spectroscopy spectra of OLHP films treated with the different cations (right). Red circles indicate the additional electronic states. Adapted with permission from (96). a.u., arbitrary units; PRA, pyrene-ammonium; PRMA, pyrene-methylammonium; PREA, pyrene-ethylammonium.

the utility of trial-and-error approaches and to maximize beneficial improvements. In addition to their contributions to hydrophobicity and defect passivation, important breakthroughs in recent years have been realized by A cation surface modification. The top surface of OLHP films forms a carrier-extraction interface with a contacting charge-selective layer, typically a hydrophobic organic material. Surface modification by A cations can be used to aid the assembly of the charge-transporting layer and improve interfacial contact, by tailoring the interaction between the charge-transporting layer species and specific moieties on the A cation. This is exemplified by the use of n-hexyl-trimethylammonium (HTA+) to facilitate the self-assembly of poly(3-hexylthiophene) (P3HT) (92). Interdigitation of the hydrophobic hexyl (–C6H13) backbone chains contained Lee et al., Science 375, eabj1186 (2022)

on both HTA+ and P3HT promoted the growth of P3HT with a fibril structure. The fibril structure was suggested to enhance the chargeextraction capability of P3HT as a dopant-free hole-transporting material. This notable breakthrough resulted in one of the previous worldrecord performance PSCs (green dot in Fig. 5A). Relatedly, A cations can also be used to manipulate the OLHP surface energy. This can be exploited to induce the preferential growth of specific crystallographic planes with lower energy. During a secondary graingrowth process, BA+, octylammonium, and oleylammonium progressively decreased the (100) plane surface energy to promote the recrystallization of highly textured (100) grains with greatly enlarged grain sizes (Fig. 5C) (93). Secondary surface grain growth has also been reported for A cations paired with Br– as the

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counter anion, including GABr (84), FABr (83), and MABr (94). Such grain recrystallization can effectively minimize surface pinhole and/or PbI2 formation (84). More generally, rather than the ubiquitous I– (or Br – ), pairing A cations with alternative counter anions presents further opportunities to modify the OLHP surface, in addition to avoiding the possible formation of iodine interstitial defects as a side effect (61). For instance, sulfate (SO42–) and phosphate (PO43–) counter anions [paired with octylammonium (OA+)] were reported to form thin (29% efficiency by enhanced hole extraction. Science 370, 1300–1309 (2020). doi: 10.1126/science. abd4016; pmid: 33303611 D. Kim et al., Efficient, stable silicon tandem cells enabled by anion-engineered wide-bandgap perovskites. Science 368, 155–160 (2020). doi: 10.1126/science.aba3433; pmid: 32217753 G. E. Eperon et al., Perovskite-perovskite tandem photovoltaics with optimized band gaps. Science 354, 861–865 (2016). doi: 10.1126/science.aaf9717; pmid: 27856902

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Funding: This work was supported by a Korea Institute of Energy Technology Evaluation and Planning (KETEP) grant funded by the Korean government (MOTIE) under award numbers 20213030010400 and 20214000000640 (J.-W.L.); by National Research Foundation of Korea grants NRF-2018R1A3B1052820 (S.I.S.) and NRF-2021R1A3B1076723 (N.-G.P.); and by the US Department of Energy’s Office of Energy Efficiency and Renewable Energy (EERE) under the Solar Energy Technologies Office under award number DE-EE0008751 (S.T. and Y.Y.) Competing interests: The authors declare that they have no competing interests. 10.1126/science.abj1186

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RESEARCH ARTICLE SUMMARY

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HUMAN EVOLUTION

A unified genealogy of modern and ancient genomes Anthony Wilder Wohns, Yan Wong†, Ben Jeffery, Ali Akbari, Swapan Mallick, Ron Pinhasi, Nick Patterson, David Reich, Jerome Kelleher†, Gil McVean*†

INTRODUCTION: The characterization of modern and ancient human genome sequences has revealed previously unknown features of our evolutionary past. As genome data generation continues to accelerate—through the sequencing of population-scale biobanks and ancient samples from around the world—so does the potential to generate an increasingly detailed understanding of how populations have evolved. However, such genomic datasets are highly heterogeneous. Samples from diverse times, geographic locations, and populations are processed, sequenced, and analyzed using a variety of techniques. The resulting datasets

contain genuine variation but also complex patterns of missingness and error. This makes combining data challenging and hinders efforts to generate the most complete picture of human genomic variation. RATIONALE: To address these challenges, we use the foundational notion that the ancestral relationships of all humans who have ever lived can be described by a single genealogy or tree sequence, so named because it encodes the sequence of trees that link individuals to one another at every point in the genome. This tree sequence of humanity is immensely

complex, but estimates of the structure are a powerful means of integrating diverse datasets and gaining greater insights into human genetic diversity. In this work, we introduce statistical and computational methods to infer such a unified genealogy of modern and ancient samples, validate the methods through a mixture of computer simulation and analysis of empirical data, and apply the methods to reveal features of human diversity and evolution. RESULTS: We present a unified tree sequence of 3601 modern and eight high-coverage ancient human genome sequences compiled from eight datasets. This structure is a lossless and compact representation of 27 million ancestral haplotype fragments and 231 million ancestral lineages linking genomes from these datasets back in time. The tree sequence also benefits from the use of an additional 3589 ancient samples compiled from more than 100 publications to constrain and date relationships. Using simulations and empirical analyses, we demonstrate the ability to recover relationships between individuals and populations as well as to identify descendants of ancient samples. We calculate the distribution of the time to most recent common ancestry between the 215 populations of the constituent datasets, revealing patterns consistent with substantial variation in historical population size and evidence of archaic admixture in modern humans. The tree sequence also offers insight into patterns of recurrent mutation and sequencing error in commonly used genetic datasets. We find pervasive signals of sequencing error as well as a small subset of variant sites that appear to be erroneous. Finally, we introduce an estimator of ancestor geographic location that recapitulates key features of human history. We observe signals of very deep ancestral lineages in Africa, the out-of-Africa event, and archaic introgression in Oceania. The method motivates improved spatiotemporal inference methods that will better elucidate the paths and timings of historic migrations. CONCLUSION: The profusion of genetic sequencing data creates challenges for integrating diverse data sources. Our results demonstrate that whole-genome genealogies provide a powerful platform for synthesizing genetic data and investigating human history and evolution.

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Visualizing inferred human ancestral lineages over time and space. Each line represents an ancestordescendant relationship in our inferred genealogy of modern and ancient genomes. The width of a line corresponds to how many times the relationship is observed, and lines are colored on the basis of the estimated age of the ancestor. 836

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The list of author affiliations is available in the full article online. *Corresponding author. Email: [email protected] These authors contributed equally to this work. Cite this article as A. W. Wohns et al., Science 375, eabi8264 (2022). DOI: 10.1126/science.abi8264

READ THE FULL ARTICLE AT https://doi.org/10.1126/science.abi8264 science.org SCIENCE

RES EARCH

RESEARCH ARTICLE

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HUMAN EVOLUTION

A unified genealogy of modern and ancient genomes Anthony Wilder Wohns1,2, Yan Wong2†, Ben Jeffery2, Ali Akbari1,3,4, Swapan Mallick1,5, Ron Pinhasi6, Nick Patterson1,3,4,5, David Reich1,3,4,5, Jerome Kelleher2†, Gil McVean2*† The sequencing of modern and ancient genomes from around the world has revolutionized our understanding of human history and evolution. However, the problem of how best to characterize ancestral relationships from the totality of human genomic variation remains unsolved. Here, we address this challenge with nonparametric methods that enable us to infer a unified genealogy of modern and ancient humans. This compact representation of multiple datasets explores the challenges of missing and erroneous data and uses ancient samples to constrain and date relationships. We demonstrate the power of the method to recover relationships between individuals and populations as well as to identify descendants of ancient samples. Finally, we introduce a simple nonparametric estimator of the geographical location of ancestors that recapitulates key events in human history.

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ur ability to determine relationships among individuals, populations, and species is being transformed by populationscale biobanks of medical samples (1, 2), collections of thousands of ancient genomes (3), and efforts to sequence millions of eukaryotic species for comparative genomic analyses (4). Such relationships, and the resulting distributions of genetic and phenotypic variation, reflect the complex set of selective, demographic, and molecular processes and events that have shaped species such as our own (5–8). However, learning about evolutionary events and processes from the totality of genomic variation, in humans or other species, is challenging. Combining information from multiple datasets, even within a species, is technically demanding: Discrepancies between cohorts due to error (9), differing sequencing techniques (10, 11), and variant processing (12) can lead to noise that can easily obscure genuine signal. Furthermore, few tools can cope with the vast datasets that arise from the combination of multiple sources (13). Also, statistical analysis typically relies on data-reduction techniques (14, 15) or the fitting of parametric models (16–19), which may provide an incomplete picture of the complexities of evolutionary history. Finally, data access and governance restrictions often limit the ability to combine data sources (20). 1

Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA. 2Big Data Institute, Li Ka Shing Centre for Health Information and Discovery, University of Oxford, Oxford OX3 7LF, UK. 3Department of Human Evolutionary Biology, Harvard University, Cambridge, MA 02138, USA. 4 Department of Genetics, Harvard Medical School, Boston, MA 02115, USA. 5Howard Hughes Medical Institute, Harvard Medical School, Boston, MA 02115, USA. 6Department of Evolutionary Anthropology, University of Vienna, 1090 Vienna, Austria. *Corresponding author. Email: [email protected] These authors contributed equally to this work.

Wohns et al., Science 375, eabi8264 (2022)

The succinct tree sequence data structure provides a potential solution to many of these problems (13, 21). Tree sequences extend the fundamental concept of a phylogenetic tree to multiple correlated trees along the genome, which is necessary when considering genealogies within recombining organisms (22). Notably, the tree sequence and the mapping of mutation events to it reflects the totality of what is knowable about genealogical relationships and the evolutionary history of individual variants. A tree sequence is defined as a graph with a set of nodes representing sampled chromosomes and ancestral haplotypes, edges connecting nodes representing lines of descent, and variable sites containing one or more mutations mapped onto the edges (Fig. 1A). Recombination events in the ancestral history of the sample create different edges and thus distinct but highly correlated trees along the genome. Tree sequences can not only be used to compress genetic data (13) but also lead to highly efficient algorithms for calculating population genetic statistics (23). A unified genealogy of modern and ancient human genomes

Here, we introduce, validate, and apply nonparametric methods for inferring time-resolved tree sequences from multiple heterogeneous sources to efficiently infer a single, unified tree sequence of ancient and contemporary human genomes. Although humans are the focus of this study, the methods and approaches we introduce are valid for most recombining organisms. To generate a unified genealogy of modern and ancient human genomes, we integrated data from three modern datasets: the 1000 Genomes Project (TGP), which contains 2548 sequenced individuals from 26 populations (6); the Human Genome Diversity Project (HGDP), which consists of 929 se-

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quenced individuals from 54 populations (8); and the Simons Genome Diversity Project (SGDP), with 278 sequenced individuals from 142 populations (7). In total, 154 individuals appear in more than one of these datasets (24). Additionally, we included data from three high-coverage sequenced Neanderthal genomes (25–27), a single Denisovan genome (28), and high-coverage whole-genome data from a nuclear family of four (a mother, a father, and their two sons, with average coverages of 10.8×, 25.8×, 21.2×, and 25.3×, respectively) from the Afanasievo culture, who lived ∼4.6 thousand years ago (ka) in the Altai Mountains of Russia (table S1). Finally, we used 3589 published ancient samples from >100 publications compiled by the Reich Laboratory (24) and three sequenced ancient samples—Loschbour, LBK-Stuttgart, and Ust’Ishim (5, 29)—to constrain allele age estimates. These ancient genomes were not included in the final tree sequence because of the lack of reliable phasing for most of the samples. We built a unified genealogy from these datasets using an iterative approach (Fig. 1B). We first merged the modern datasets and inferred a tree sequence for each autosome using tsinfer, version 0.2 (24, 30). We then estimated the age of ancestral haplotypes with tsdate, a Bayesian approach that infers the age of ancestral haplotypes with good accuracy and scaling properties (Fig. 1C and figs. S1 to S5) (24, 31). Notably, tsdate can be used to date any valid tree sequence, not only those inferred by tsinfer. tsdate can also use ancient samples to improve date estimates (Fig. 1D). We identified 6,412,717 variants present in both ancient and modern samples. A lower bound on variant age is provided by the estimated archaeological date of the oldest ancient sample in which the derived allele is found. Where this was inconsistent with the initial inferred value (for 559,431 or 8.7% of variants), we used the archaeological date as the variant age. Finally, we integrated the Afanasievo family and four archaic sequences with the modern samples and reinferred the tree sequence. The Afanasievo family has high coverage and comparably reliable haplotype phasing and was included to demonstrate the ability of our approach to incorporate high-quality ancient samples. The integrated tree sequences of each autosome combined contain 26,958,720 inferred ancestral haplotype fragments, 231,073,278 edges, 91,172,114 variable sites, and 245,631,834 mutations. We infer that 38.7% of variant sites require more than one change in allelic state in the tree sequence to explain the data. This may indicate either recurrent mutations or errors, all of which are represented by additional mutations in the tree sequence. If we discount mutations that are likely indicative of sequencing errors (24), we find that 1 of 9

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Fig. 1. Schematic overview and validation of the inference methodology. (A) An example tree sequence topology with four samples (nodes 0 to 3), two marginal trees, four ancestral haplotypes (nodes 4 to 7), and two mutations. Tspan measures the genomic span of each marginal tree topology, with the dotted line indicating the location of a recombination event. The graph representation is equivalent to the tree representation. (B) Schematic representation of the inference methodology. Step 0: Alleles are ordered by frequency (freq.); the mutation represented by the four-point star is considered to be older. Step 1: The tree sequence topology is inferred with tsinfer using modern samples. Step 2: The tree sequence is dated with tsdate. Step 3: Node date estimates are constrained with the known age of ancient samples. Step 4: Ancestral haplotypes are reordered by the estimated age of their focal mutation; the five-pointed star mutation is now inferred to be older. The

13,513,873 sites contain at least two mutations affecting more than one sample, which implies that up to 17.5% of variable sites could result from more than one ancestral mutation. A high proportion of sites with more than ∼100 mutaWohns et al., Science 375, eabi8264 (2022)

YRI

algorithm returns to step 1 to reinfer the tree sequence topology with ancient samples. Arrows refer to modes of operation: steps 0, 1, and 2 only (red); steps 0, 1, 2, 4, 1, and 2 (green); or steps 0, 1, 2, 3, 4, 1, and 2 (blue) (24). (C) Scatter plots and accuracy metrics comparing simulated (x axis) and inferred (y axis) mutation ages from msprime neutral coalescent simulations, using tsdate with the simulated topology (left) and inferred topology from tsinfer (right). RMSLE, root mean squared log error. (D) Accuracy metrics, RMSLE (top), and Spearman rank correlation coefficient (r) (bottom), with modern samples only (first panel), after one round of iteration (second panel), and with increasing numbers of ancient samples (third panel) [colored arrows as in (B)]. Ancient samples from three eras of human history are considered, as in the schematic (24). CEU, Utah residents with Northern and Western European Ancestry; CHB, Han Chinese; YRI, Yorubans.

tions on chromosome 20 have sequencing or alignment quality issues as defined by the TGP accessibility mask (6) or are in minimal linkage disequilibrium to their surrounding sites (fig. S6), which suggests that they are

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CHB

largely erroneous. Moreover, analysis of data simulated with an empirically calibrated error profile and evaluation of the enrichment of multiple mutations at sites with known elevated mutation rates suggests that most of 2 of 9

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the multiple mutations we identify are likely explained by error, but a minority (~20%) are the result of genuine recurrence or back mutation (24). We chose to retain such sites so that our inferred tree sequences are lossless representations of the original data sources; however, future iterative approaches to the removal of such probable errors are likely to improve use cases, such as imputation. To characterize fine-scale patterns of relatedness between the 215 populations of the

constituent datasets, we estimated the time to the most recent common ancestor (TMRCA) between pairs of haplotypes from these populations at the 122,637 distinct trees in the tree sequence of chromosome 20 (∼300 billion pairwise TMRCAs). In this and other analyses, we present data from this chromosome because they are representative of genome-wide patterns. After performing hierarchical clustering on the average pairwise TMRCA values, we find that samples do not cluster by data

source (which would indicate artifacts) but reflect patterns of global relatedness (Fig. 2 and the external interactive figure). We conclude that our method of integrating datasets is therefore robust to biases introduced by different datasets. In this genealogy, numerous features of human history are immediately apparent, such as the deep divergence of archaic and modern humans, the effects of the out-of-Africa event (Fig. 2A), and a subtle increase in Oceanian and

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Fig. 2. Clustered heatmap showing the average TMRCA on chromosome 20 for haplotypes within pairs of the 215 populations in the HGDP, TGP, SGDP, and ancient samples. Each cell in the heatmap is colored by the logarithmic mean TMRCA of samples from the two populations. Hierarchical clustering of rows and columns has been performed using the unweighted pair group method with arithmetic mean (UPGMA) algorithm on the value of the pairwise average TMRCAs. Row colors are given by the region of origin for each population, as shown in the legend. The source of genomic samples for each population is indicated in the shaded boxes above the column labels. Three population relationships are highlighted using span-weighted histograms of the TMRCA distributions: (A) Average distribution of TMRCAs between all non-African populations (black line) Wohns et al., Science 375, eabi8264 (2022)

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compared with African/African TMRCAs (solid yellow). (B) Denisovan and Papuan/Australian TMRCAs (solid line) compared with the Denisovan against all nonarchaic populations (solid white). This subtle but specific signal of elevated recent ancestry between the Denisovan and Papuans/Australians is particularly evident in the external interactive figure. (C) TMRCAs between the two Samaritan chromosomes (solid line) compared with the Samaritans/all other modern humans (solid white). Selected populations with particularly recent within-group TMRCAs are indicated. Duplicate samples appearing in more than one modern dataset are included in this analysis. The external interactive figure is an interactive version of this figure that is available at https://awohns.github.io/ unified_genealogy/interactive_figure.html. 3 of 9

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Denisovan most recent common ancestor (MRCA) density from 2000 to 5000 generations ago (Fig. 2B). Multiple populations show recent within-group TMRCAs, which is suggestive of recent bottlenecks or consanguinity. The most extreme cases occur when a population consists of a single individual in our dataset, such as the Samaritan individual from the SGDP, where we see a logarithmic average within-group TMRCA of ∼1000 generations, which is caused by multiple MRCAs at very recent times (Fig. 2C) and is consistent with a severe bottleneck and consanguinity in recent centuries (32). Indigenous populations in the Americas, an Atayal individual from Taiwan, and Papuans also exhibit particularly recent within-group TMRCAs (Fig. 2). Tree sequenceÐbased analysis of descent from ancient sequences

To validate the dating methodology, we used simulations to show that the integration of ancient samples improves derived allele age estimates under a range of demographic his-

tories (Fig. 1D). To provide empirical validation of the method, we tested how best to infer allele ages that are consistent with observations from ancient samples. Thus, we inferred and dated a tree sequence of TGP chromosome 20 (without using ancient samples) and compared the resulting point estimates and upper and lower bounds on allele age with results from GEVA (33) and Relate (34). This resulted in a set of 659,804 variant sites where all three methods provide an allele age estimate. Of these, 76,889 derived alleles are observed within the combined set of 3734 ancient genome samples, thus putting a lower bound on allele age. The estimated allele ages from tsdate and Relate showed the greatest compatibility with ancient lower bounds, despite the fact that the mean age estimate from tsdate is more recent than that of Relate (Fig. 3A) (24). Next, to assess the ability of the unified tree sequence to recover known relationships between ancient and modern populations, we considered the patterns of descent to modern samples from Archaic sequences on

chromosome 20. Simulations indicate that this approach detects introgressed genetic material from Denisovans at a precision of ∼86% with a recall of ∼61% (24). We find descendants among nonarchaic individuals, including both modern individuals and the Afanasievo, for 13% of the span of the Denisovan haplotypes on chromosome 20. The highest degree of descent among modern humans is in Oceanian populations, as previously reported (28, 35Ð37) (Fig. 3B). However, the tree sequence also reveals how both the extent and nature of descent from Denisovan haplotypes vary greatly among modern humans. In particular, we find that Papuans and Australians carry multiple fragments of Denisovan haplotypes that are largely specific to the individual (Fig. 3C). By contrast, other modern descendants of Denisovan haplotypes have fewer blocks that are more widely shared, often between geographically distant individuals. Examining the other ancient samples in the unified genealogy, we find the greatest amount of descent from the haplotypes of the Afanasievo

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Fig. 3. Validation of inference methods using ancient samples. (A) Comparison of mutation age estimates from tsdate, Relate, and GEVA with 3734 ancient samples at 76,889 variants on chromosome 20 (note that Relate estimates ages separately for each population in which a variant is found). The radiocarbondated age of the oldest ancient sample carrying a derived allele at each variant site in the TGP is used as the lower bound on the age of the mutation (diagonal lines). Mutations below this line have an estimated age that is inconsistent with the age of the ancient sample. Black lines on each plot show Wohns et al., Science 375, eabi8264 (2022)

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the moving average of allele age estimates from each method as a function of oldest ancient sample age. Plots to the left show the distribution of allele age estimates for modern-only variants from each respective method. Additional metrics are reported in each plot. (B) Percentage of chromosome 20 for modern samples in each region that is inferred to descend from Denisovan haplotypes, calculated with the genomic descent statistic (57). (C) Tracts of descent along chromosome 20 descending from Denisovan haplotypes in modern samples with at least 100 kilobases (kb) of total descent (colors as in Fig. 2). 4 of 9

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family among individuals in Western Eurasia and South Asia (fig. S7A), consistent with findings from the genetically similar Yamnaya peoples and supporting a contemporaneous diffusion of Afanasievo-like genetic material via multiple routes (38). For the Neanderthals, where there are three samples of different ages, our simulations indicate that interpretation of the descent statistics is complicated by varying levels of precision and recall among lineages. Nevertheless, recall is highest at regions where introgressing and sampled archaic lineages share more recent common ancestry, and precision is higher for the Vindija sample, which is more closely related to introgressing lineages. Examining patterns of descent from Vindija haplotypes across autosomes indicates that modern non-African groups carry similar levels of Vindija-like material (fig. S8), which supports suggestions that the proportions are similar between East Asians and West Eurasians (39) and is inconsistent with other studies (26, 40). Nonparametric inference of spatiotemporal dynamics in human history

Tree sequence–based analysis of ancient samples demonstrates an ability to characterize

patterns of recent descent. We developed a simple estimator of ancestor spatial location that uses the coordinates of descendants of a node combined with the structure of the tree sequence to provide an estimate of ancestors’ geographic position (24). Briefly, this is accomplished by determining the coordinates of a parent node in the tree sequence as the midpoint of its immediate children (24), an approach that performs well in simple simulations (fig. S9). The approach can use information on the location of ancient samples, although it does not attempt to capture the geographical plausibility of different locations and routes. The inferred locations are thus a model-free estimate of ancestors’ locations, informed by the tree sequence topology and geographic distribution of samples. We applied our method to the unified tree sequence of chromosome 20, excluding TGP individuals (which lack precise location information). We found that the inferred ancestor location recovers multiple key events in human history (Fig. 4 and movie S1). Despite the fact that the geographic center of sampled individuals is in Central Asia, by 72 ka, the average location of ancestral haplotypes is in Northeast Africa and remains there until the oldest com-

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mon ancestors are reached. In fact, the inferred geographic center of gravity of the 100 oldest ancestral haplotypes (which have an average age of ∼2 million years) is located in Sudan at 19.4°N, 33.7°E. These findings reflect the depth of African lineages in the inferred tree sequence and are compatible with well-dated early modern human fossils from eastern and northern Africa (41, 42). We caution that if we analyzed data from a grid sampling of populations in Africa, the geographic center of gravity of independent lineages at different time depths would shift. Additionally, migrations occurring within the past few thousand years (43, 44) mean that presentday distributions of groups in Africa and elsewhere may not represent those of their ancestors, and thus we may have a distorted picture of ancient geographic distributions (45). Nevertheless, the deep tree structure is geographically centered in Africa in autosomal data, just as it is for mitochondrial DNA and Y chromosomes (46, 47). By 280 ka, the estimated geographic center of human ancestors is still located in Africa, but many ancestors are also observed in the Middle East and Central Asia, and a few are located in Papua New Guinea. At 140 ka, more ancestors

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Fig. 4. Visualization of the nonparametric estimator of ancestor geographic location for HGDP, SGDP, Neanderthal, Denisovan, and Afanasievo samples on chromosome 20. (A) Geographic location of samples used to infer ancestral geography. The size of each symbol is proportional to the number of samples in that population. (B) The average location of the ancestors of each HGDP population from time t = 0 to ~2 million years ago. The width of lines is proportional to the number of ancestors of each Wohns et al., Science 375, eabi8264 (2022)

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population over time. The ancestor of a population is defined as an inferred ancestral haplotype with at least one descendant in that population. (C) Two-dimensional histograms showing the inferred geographical location of HGDP ancestral lineages at six time points. Histogram bins with 1 and h < 1 translates into an enhancement of the ratio of decay rates G32/G31 in the PhC sample. After comparing model parameters

results are compiled in Fig. 3E, where the green peak scintillation always dominates (h > 1) for the TF sample, whereas a crossover is seen for a certain value of the deposited beam power (represented by h crossing unity) for the PhC sample. To account for these observations, we consider a description of the defect levels in terms of a three-level Fermi system, featuring two lowest occupied levels (denoted 1 and 2 in Fig. 3C) coupled to an upper “pump” level (denoted 3) through the high-energy electron beam, which acts as a pump. These three levels correspond to energy levels from our electronic structure calculations of the STH defects in silica [based on DFT (39)]. The relative rates of the transitions 3 → 1 (G31) and 3 → 2 (G32)— which depend on the pump strength and the emission rates (which in turn depend on Veff)— dictate the strength of the green and red em-

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Fig. 2. Experimental demonstration of nanophotonic shaping and enhancement of electron beamÐinduced scintillation. (A) A modified scanning electron microscope (SEM) is used to induce and measure scintillation from electron beams (10 to 40 keV) bombarding scintillating nanophotonic structures. (B) Electron energy loss in the silicon-on-insulator wafer is calculated via Monte Carlo simulations. Inset: Zoomed-in electron energy loss in the scintillating (silica) layer. a.u., arbitrary units. (C) SEM images of photonic crystal (PhC) sample (etch depth 35 nm). Tilt angle 45°. Scale bars, 1 µm (top), 200 nm Roques-Carmes et al., Science 375, eabm9293 (2022)

polarizer

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(bottom). (D) Scintillation spectrum from thin-film and PhC samples with varying etch depths (but same thickness). PSD, power spectral density. (E) The scintillation signal is coupled out of the vacuum chamber with an objective and then imaged on a camera and analyzed with a spectrometer. (F and G) Comparison between theoretical (left) and experimental (right) scintillation spectra for green and red scintillation peaks. Inset: Calculated scintillation spectra (per solid angle) at normal emission direction, showing the possibility of much larger enhancements over a single angle of emission. 4 of 8

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Fig. 3. Probing the microscopics of electron beamÐinduced scintillation in silica. (A) Energy-dependent scintillation spectra (PhC sample, etch 25 nm). (B) Top: 3D molecular model of STH defect in silica; r, spin-polarized density. Bottom: Calculated STH defect energy levels via density functional theory (DFT). (C) Simplified three-level system modeling the microscopics of scintillation from STH defects in silica. (D) Bulk scintillation spectrum calculated with DFT (dipole matrix elements). (E) Thin film (left) and PhC (right) scintillation peak ratios as a function of deposited beam powers through electron pumping. The dashed line corresponds to the mean model prediction and the shaded area to the prediction from the model parameters ± SD [defined as the uncertainty on G31/G32, the ratio of rates shown in (B), bottom]. Inset: Maximum signal of green and red scintillation peaks versus current in TF sample.

fitting the TF experimental data to models fitting the PhC data, we estimate that the decay rate ratio is enhanced by a factor of ~2.3 ± 1.0. This value is in agreement with the Veff enhancement predicted by our theory and by our observation of enhanced scintillation from the red defects in the experimental data. By patterning nanophotonic scintillators, one can thus tailor microscopic properties and selectively enhance scintillation from microscopic defects. This also suggests that scintillation rates can be selectively enhanced using nanophotonic structures, a feature that is particularly sought after in some medical imaging modalities (43). Moreover, our results indicate that the measured scintillation may be used to sort out competing models of the electronic structure, especially in complex defects such as this one, where self-interaction effects lead to modeling difficulties (39). Roques-Carmes et al., Science 375, eabm9293 (2022)

Observation of strongly enhanced scintillation induced by x-rays

We now consider another example of a nanophotonic scintillator designed using our theoretical framework, showing its application to enhancing scintillation induced by high-energy photons such as x-rays. Such HEPs lose their energy much differently from massive charged particles (such as electrons). In our experimental configuration (Fig. 4A), x-rays traverse a specimen, leading to spatially dependent absorption of the incident x-ray flux. This absorption pattern is geometrically magnified until it encounters the cerium-doped yttrium-aluminum-garnet (YAG:Ce) scintillator. The pattern is then translated into scintillation photons, which are imaged with an objective and a charge-coupled device (CCD) camera. The nanopatterned scintillator is constructed by etching a two-dimensional PhC 25 February 2022

into YAG [via focused ion beam (FIB) lithography (39)] at the surface of the scintillator facing the objective. The PhC period is 430 nm and the total patterned area is 215 µm × 215 µm (Fig. 4) or 430 µm × 430 µm (Fig. 5). In the case of YAG:Ce, the intrinsic scintillation properties have long been characterized and our experiments reveal only weak dependence of the scintillation on incident x-ray energy (39). Thus, the full theoretical apparatus we demonstrate for electron scintillation is not needed to adequately describe our results. Primarily, the electromagnetic response (using reciprocity) is needed to account for the experimental results and is the part of our general framework that leads us to order-of-magnitude enhancement of x-ray scintillation (39). According to the scintillation framework developed above, nanophotonic scintillation enhancement is to be expected when the absorption of light is enhanced. In Fig. 4B, we show the calculated wavelength-dependent scintillation in YAG:Ce (averaged over the angular acceptance of the objective, as in Fig. 2) for an unpatterned self-standing thick (20 µm) film, as well as for the PhC sample. Here, the calculated enhancement is by a factor of ~9.3 ± 0.8 over the measured scintillation spectrum. In our calculations, we attribute the main error bar to the uncertainty on the hole depth [±10 nm, as can be extracted from our atomic force microscopy (AFM) measurements, shown fully in Fig. 4A (right) and in cross sections in (39)]. However, there are several other sources of uncertainty in the fabricated samples: the hole diameter, the hole periodicity, and the optical absorption of YAG:Ce (taken in our calculations to be the value provided by the wafer supplier). We also measured, and compared to our theory, scintillation enhancements from multiple nanophotonic scintillators with various thicknesses, hole shapes, depths, and patterned areas (table S1) (39). Here, the x-ray scintillation enhancement originates in light out-coupling enhancement (or, by reciprocity, in-coupling enhancement). In particular, the PhC allows more channels (i.e., a plane-wave coupling to a resonance) into the scintillator crystal than would be achievable with a flat interface. The multiple channels translate into sharp resonant peaks in the calculated absorption spectrum [see (39) for raw signal]. This is to be contrasted with the origin of electron beam–induced scintillation enhancement in silica, where the enhancement can be tied to the presence of one or a small number of high-Q resonances. This effect is of the type often leveraged to design more efficient LEDs and solar cells that approach the “Yablonovitch limit” in both rayoptical (44, 45) and nanophotonic (46, 47) settings. There, it is well known that the device efficiency is optimized by designing a structure 5 of 8

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Fig. 4. Nanophotonic enhancement of x-ray scintillation. (A) Left: X-ray scintillation experimental setup. Light generated by x-ray bombardment of a YAG:Ce scintillator is imaged with a set of free-space optics. A specimen may be positioned between the source and the scintillator to record an x-ray scan of the specimen. Right: AFM image of patterned YAG:Ce scintillator (thickness, 20 µm). Scale bar, 1 µm. (B) Calculated scintillation spectrum of the PhC, integrated over the experimental angular aperture. Calculations are performed for measured etching depths ± SD (corresponding to 40, 50, and 60 nm). The shaded area corresponds to possible scintillation enhancements between those values. The calculated spectra are convolved with a moving-mean filter of width 1.33 nm [raw signal shown in (39)]. (C) Measured scintillation along a line of the sample, including regions on (red) and off (blue) the PhC. The scintillation from the PhC region is on average higher than the unpatterned region by a factor of ~9.1. All signals were recorded with x-ray source settings of 40 kVp, 3 W.

that leads to strong absorption over the spectral range of the emission (44, 48). In Fig. 4C, we show the experimentally measured scintillation scanned along a line of the sample. The regions “off” indicate unpatterned regions of the YAG:Ce, whereas “on” indicates the PhC region. Here, the signal is enhanced on average by a factor of ~9.1 over the unpatterned region, consistent with the predictions of Fig. 4B. To demonstrate the potential of our approach to x-ray imaging, we fabricated a larger-scale pattern on a 50-µm wafer, which exhibits a scintillation enhancement of 2.3 (39). We recorded single-shot x-ray scans of biological and inorganic specimens through the PhC, showing no evident decrease in resolution, while increasing the image brightness by the same factor. Equivalently, the required x-ray dose or exposure time to get a given number of counts on the detector is reduced [shown experimentally in (39)]. Our framework allows us to further gain understanding of the scintillation mechanism at play, directly leveraging known techniques in absorption enhancement. For certain structures, one could expect even greater scintillation enhancements on the order of ~4n2 in the ray-optics approximation (44) or ~4pn2 for periodic structures on the wavelength scale (46, 47) (where n is the index of refraction). Roques-Carmes et al., Science 375, eabm9293 (2022)

For example, for a thin high-index material such as doped GaAs, which also scintillates at room temperature (49), enhancements on the order of ~50 and ~150 could be respectively achieved in the two regimes (over a 2p collection solid angle). Discussion

We have presented a general framework to model, tailor, and enhance scintillation by means of nanophotonic structures integrated into scintillating materials (nanophotonic scintillators). Although we mainly focused on the demonstration of spectral shaping and enhancement of scintillation, our results could be extended to show angular and polarization control as well. We have demonstrated nanophotonic scintillators enhancing electron beam– induced and x-ray–induced scintillation. The theoretical framework we used to describe our experimental results combines Monte Carlo simulations of the energy loss density (40) with DFT calculations of the microscopic structure and full-wave calculations of the electromagnetic response of the nanophotonic structures probed in this work. We note that this type of “full” analysis, to the best of our knowledge, has not been performed to explain scintillation (nor incoherent cathodoluminescence) experiments, likely because of the prohibitively expensive computa25 February 2022

tions associated with simulating ensembles of dipoles radiating in 3D structures. The reciprocity framework we use [also commonly used in areas of thermal radiation, LEDs, and photoluminescence (34, 50–54)] strongly simplifies the analysis, and makes a full modeling of the scintillation problem tractable. We conclude by outlining a few promising avenues of future work that are enabled by the results provided here. [See (39) for further elaboration and initial results for each of these avenues.] The first area, inspired by our simplified calculations based on reciprocity, is numerical optimization of nanophotonic scintillators. Our framework, which relies on the calculation of Veff (which is relatively amenable, even in three dimensions), enables the inverse design of nanophotonic scintillators. [See (39) for methods to calculate the forward (Veff given a nanophotonic structure) and backward (gradients of Veff with respect to degrees of freedom describing the nanophotonic structure) problems.] The experimentally reported enhancements can be further improved upon by inverse-designing the nanophotonic structure via topology optimization of Veff (55). In (39), we show the kind of results that could be expected from topology-optimized nanophotonic scintillators: We find that selective enhancements of scintillation in particular topology-optimized photonic structures by one to nearly two orders of magnitude are possible. By considering different emission linewidths and frequencies, one can selectively design optimized nanophotonic structures that enhance one of the scintillating peaks, at a single frequency or over the entire scintillation bandwidth. Beyond our reciprocity-based approach, low-rank methods can be used for the inverse design of nanophotonic scintillators with very large angular ranges (56, 57). Beyond scintillation, our techniques may find applicability in other imaging modalities involving random incoherent emitters, such as surface-enhanced Raman scattering (58). Another promising area of research enabled by our findings is nanophotonically enhanced and controlled UV light sources. In (39) we show how UV scintillation in patterned materials such as hBN enables strongly enhanced scintillation with a spectrum that can be controlled simply by the position of the electron beam relative to the patterned features in the hBN arising from changes in the overlap between the HEP loss density and Veff. The prospect of realizing optimized and compact nanophotonic UV scintillation sources is particularly exciting for applications in water purification and sanitization (59). Nanophotonic scintillators provide a versatile approach for controlling and enhancing the performance of scintillating materials for a wide range of applications. The framework developed here applies to arbitrary scintillating 6 of 8

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Fig. 5. X-ray scintillation imaging with nanophotonic scintillators. (A and B) Measured x-ray images of a TEM grid on scotch tape (A) and a flower bud (B). The white square delimits the PhC area. (C and D) Flat field–corrected zoom-in of the x-ray image in the PhC area. Geometric magnification on those images is ~2. Relative to the unpatterned regions, the images are brighter above the PhC region, showing no evident decrease in resolution. The particular nanophotonic scintillator used for this experiment was patterned over an area of 430 µm × 430 µm and resulted in a scintillation enhancement of ×2.3 (measured with respect to an unpatterned scintillator of same thickness). All signals were recorded with x-ray source settings of 60 kVp, 5 W.

materials, nanophotonic structures, and HEPs, solving for the process end-to-end using firstprinciples methods. The electron-beam and x-ray scintillation experiments provide the proof-of-concept tests of the promising prospects of this field. Our work may open a panoply of exciting applications, from highresolution, low-dose x-ray imaging to efficient UV electron beamÐpumped light sources. RE FE RENCES AND N OT ES

1. A. Gektin, M. Korzhik, Inorganic Scintillators for Detector Systems (Springer, 2017). 2. S. Cherry, J. Sorenson, M. Phelps, Physics in Nuclear Medicine (Wiley, 2012). 3. Q. Chen et al., All-inorganic perovskite nanocrystal scintillators. Nature 561, 88–93 (2018). doi: 10.1038/s41586-018-0451-1; pmid: 30150772 4. Y. Kurman, A. Shultzman, O. Segal, A. Pick, I. Kaminer, Photonic-Crystal Scintillators: Molding the Flow of Light to Enhance X-Ray and g-Ray Detection. Phys. Rev. Lett. 125, 040801 (2020). doi: 10.1103/PhysRevLett.125.040801; pmid: 32794818 5. E. Yablonovitch, Inhibited spontaneous emission in solid-state physics and electronics. Phys. Rev. Lett. 58, 2059–2062 (1987). doi: 10.1103/PhysRevLett.58.2059; pmid: 10034639 6. J. D. Joannopoulos, S. G. Johnson, J. N. Winn, R. D. Meade, Photonic Crystals: Molding the Flow of Light (Princeton Univ. Press, 2011). 7. M. Pelton, Modified spontaneous emission in nanophotonic structures. Nat. Photonics 9, 427–435 (2015). doi: 10.1038/ nphoton.2015.103 8. A. Polman, H. A. Atwater, Photonic design principles for ultrahigh-efficiency photovoltaics. Nat. Mater. 11, 174–177 (2012). doi: 10.1038/nmat3263; pmid: 22349847 9. P. Anger, P. Bharadwaj, L. Novotny, Enhancement and quenching of single-molecule fluorescence. Phys. Rev. Lett. 96, 113002 (2006). doi: 10.1103/PhysRevLett.96.113002; pmid: 16605818

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23. Y. Yang et al., Observation of enhanced free-electron radiation from photonic flatband resonances. arXiv 2110.03550 (2021). 24. X. Chen et al., Enhanced light extraction of plastic scintillator using large-area photonic crystal structures fabricated by hot embossing. Opt. Express 26, 11438–11446 (2018). doi: 10.1364/OE.26.011438; pmid: 29716062 25. A. Knapitsch et al., Results of Photonic Crystal Enhanced Light Extraction on Heavy Inorganic Scintillators. IEEE Trans. Nucl. Sci. 59, 2334–2339 (2012). doi: 10.1109/TNS.2012.2184556 26. A. Knapitsch, P. Lecoq, Review on photonic crystal coatings for scintillators. Int. J. Mod. Phys. A 29, 1430070 (2015). doi: 10.1142/S0217751X14300701 27. Z. Zhu et al., Enhanced light extraction of scintillator using large-area photonic crystal structures fabricated by soft-X-ray interference lithography. Appl. Phys. Lett. 106, 241901 (2015). doi: 10.1063/1.4922699 28. P. Pignalosa, B. Liu, H. Chen, H. Smith, Y. Yi, Giant light extraction enhancement of medical imaging scintillation materials using biologically inspired integrated nanostructures. Opt. Lett. 37, 2808 (2012). doi: 10.1364/OL.37.002808; pmid: 22825141 29. Z. Zhu et al., Improved light output from thick b-Ga2O3 scintillation crystals via graded-refractive-index photonic crystals. Opt. Express 29, 18646 (2021). doi: 10.1364/ OE.428671; pmid: 34154117 30. X. Ouyang et al., Enhanced light output of CsI(Na) scintillators by photonic crystals. Nucl. Instrum. Methods Phys. Res. A 969, 164007 (2020). doi: 10.1016/j.nima.2020.164007 31. C. A. Klein, Bandgap Dependence and Related Features of Radiation Ionization Energies in Semiconductors. J. Appl. Phys. 39, 2029 (1968). doi: 10.1063/1.1656484 32. A. Polman, M. Kociak, F. J. García de Abajo, Electron-beam spectroscopy for nanophotonics. Nat. Mater. 18, 1158–1171 (2019). doi: 10.1038/s41563-019-0409-1; pmid: 31308514 33. P. Wurfel, The chemical potential of radiation. J. Phys. C 15, 3967–3985 (1982). doi: 10.1088/0022-3719/15/18/012 34. J. J. Greffet, P. Bouchon, G. Brucoli, F. Marquier, Light Emission by Nonequilibrium Bodies: Local Kirchhoff Law. Phys. Rev. X 8, 021008 (2018). doi: 10.1103/PhysRevX.8.021008 35. D. L. Sounas, A. Alù, Non-reciprocal photonics based on time modulation. Nat. Photonics 11, 774–783 (2017). doi: 10.1038/ s41566-017-0051-x 36. L. Zhu, S. Fan, Persistent Directional Current at Equilibrium in Nonreciprocal Many-Body Near Field Electromagnetic Heat Transfer. Phys. Rev. Lett. 117, 134303 (2016). doi: 10.1103/ PhysRevLett.117.134303; pmid: 27715122 37. D. L. C. Chan, M. Soljacić, J. D. Joannopoulos, Direct calculation of thermal emission for three-dimensionally periodic photonic crystal slabs. Phys. Rev. E 74, 036615 (2006). doi: 10.1103/PhysRevE.74.036615; pmid: 17025772 38. This issue is compounded by the sensitivity of the results to assumptions about the spatial and spectral distributions of the dipoles, which are related to the microscopic details of the defect electronic structure, as well as the mechanism of highenergy particle energy transfer into the material. 39. See supplementary materials. 40. H. Demers et al., Three-dimensional electron microscopy simulation with the CASINO Monte Carlo software. Scanning 33, 135–146 (2011). doi: 10.1002/sca.20262; pmid: 21769885 41. S. Girard et al., Overview of radiation induced point defects in silica-based optical fibers. Rev. Phys. 4, 100032 (2019). doi: 10.1016/j.revip.2019.100032 42. In principle, one would want to compare Veff in the TF to a “truly intrinsic” or “bulk” silica case. In that case, one would compare to silica of the same thickness (1000 nm). However, because this reference case is a thin film as well, nanophotonic shaping effects in the spectrum will inevitably be present. Comparing the Veff in the thin-film case of Fig. 2 to thin films without (i) the top Si layer or (ii) without both Si layers (see fig. S1), one finds that the TF of Fig. 2 presents slightly smaller absorption enhancement at the red peak, possibly due to the high reflectivity of the top Si layer (suppressing the amount of field that can be absorbed by the material). However, the PhC sample still shows strong shaping and enhancement relative to all TF cases. 43. P. Lecoq et al., Roadmap toward the 10 ps time-of-flight PET challenge. Phys. Med. Biol. 65, 21RM01 (2020). doi: 10.1088/1361-6560/ab9500; pmid: 32434156 44. E. Yablonovitch, Statistical ray optics. J. Opt. Soc. Am. 72, 899 (1982). doi: 10.1364/JOSA.72.000899 45. P. Campbell, M. A. Green, The limiting efficiency of silicon solar cells under concentrated sunlight. IEEE Trans. Electron Dev. 33, 234–239 (1986). doi: 10.1109/T-ED.1986.22472

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46. R. N. Raman, M. J. Matthews, J. J. Adams, S. G. Demos, Monitoring annealing via CO2 laser heating of defect populations on fused silica surfaces using photoluminescence microscopy. Opt. Express 18, 15207–15215 (2010). doi: 10.1364/OE.18.015207; pmid: 20640006 47. Z. Yu, A. Raman, S. Fan, Fundamental limit of nanophotonic light trapping in solar cells. Proc. Natl. Acad. Sci. U.S.A. 107, 17491–17496 (2010). doi: 10.1073/pnas.1008296107; pmid: 20876131 48. A. I. Zhmakin, Enhancement of light extraction from light emitting diodes. Phys. Rep. 498, 189–241 (2011). doi: 10.1016/ j.physrep.2010.11.001 49. S. Derenzo, E. Bourret, C. Frank-Rotsch, S. Hanrahan, M. Garcia-Sciveres, How silicon and boron dopants govern the cryogenic scintillation properties of N-type GaAs. Nucl. Instrum. Methods Phys. Res. A 989, 164957 (2021). doi: 10.1016/j.nima.2020.164957 50. S. Liu et al., Light-Emitting Metasurfaces: Simultaneous Control of Spontaneous Emission and Far-Field Radiation. Nano Lett. 18, 6906–6914 (2018). doi: 10.1021/acs.nanolett.8b02808; pmid: 30339762 51. K. M. Schulz, D. Jalas, A. Y. Petrov, M. Eich, Reciprocity approach for calculating the Purcell effect for emission into an open optical system. Opt. Express 26, 19247–19258 (2018). doi: 10.1364/OE.26.019247; pmid: 30114183 52. Y. Sheng et al., Čerenkov third-harmonic generation in c(2) nonlinear photonic crystal. Appl. Phys. Lett. 98, 241114 (2011). doi: 10.1063/1.3602312 53. S. Zhang et al., Calculation of the emission power distribution of microstructured OLEDs using the reciprocity theorem. Synth. Met. 205, 127–133 (2015). doi: 10.1016/j. synthmet.2015.03.035 54. A. C. Overvig, S. A. Mann, A. Alù, Thermal Metasurfaces: Complete Emission Control by Combining Local and Nonlocal Light-Matter Interactions. Phys. Rev. X 11, 021050 (2021). doi: 10.1103/PhysRevX.11.021050

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55. S. Molesky et al., Inverse design in nanophotonics. Nat. Photonics 12, 659–670 (2018). doi: 10.1038/s41566-018-0246-9 56. A. G. Polimeridis et al., Fluctuating volume-current formulation of electromagnetic fluctuations in inhomogeneous media: Incandescence and luminescence in arbitrary geometries. Phys. Rev. B 92, 134202 (2015). doi: 10.1103/ PhysRevB.92.134202 57. W. Yao, F. Verdugo, R. E. Christiansen, S. G. Johnson, Trace formulation for photonic inverse design with incoherent sources. arXiv 2111.13046 (2021). 58. R. E. Christiansen, J. Michon, M. Benzaouia, O. Sigmund, S. G. Johnson, Inverse design of nanoparticles for enhanced Raman scattering. Opt. Express 28, 4444–4462 (2020). doi: 10.1364/OE.28.004444; pmid: 32121681 59. K. Watanabe, T. Taniguchi, T. Niiyama, K. Miya, M. Taniguchi, Far-ultraviolet plane-emission handheld device based on hexagonal boron nitride. Nat. Photonics 3, 591–594 (2009). doi: 10.1038/nphoton.2009.167 60. C. Roques-Carmes et al., Data for “A framework for scintillation in nanophotonics” (2021); https://github.com/charlesrc/nanoscint. ACKN OWLED GMEN TS

We thank T. Savas for assistance in fabricating the sample used for electron-beam scintillation; I. Shestakova and O. Philip (Crytur) for helpful discussions on x-ray scintillators; C. Graf vom Hagen, X. Xu, and J. Treadgold (Zeiss) for feedback on micro-CT scanner experiments; R. Sundararaman (Rensselaer Polytechnic Institute) and J. Coulter (Harvard University) for assistance with DFT calculations; and Y. Salamin and S. Pajovic (MIT) for stimulating discussions. Funding: This material is based on work supported in part by the US Army Research Laboratory and the US Army Research Office through the Institute for Soldier Nanotechnologies under contract W911NF-18-2-0048. This material is also in part based on work supported by the Air Force Office of Scientific Research under awards FA9550-20-1-0115 and FA9550-21-1-0299. This work was performed in part on the Raith VELION FIB-SEM

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in the MIT.nano Characterization Facilities (award DMR-2117609) C.R.-C. acknowledges funding from the MathWorks Engineering Fellowship Fund by MathWorks Inc. Author contributions: C.R.-C., N.Ri., N.Ro., I.K., and M.S. conceived the original idea; N.Ri. developed the theory with inputs from C.R.-C. and A.G.; C.R.-C. and S.E.K. performed the electron-beam and x-ray experiments; C.R.-C. and N.Ri. analyzed the experimental data and fitted them to the theory; C.R.-C. and S.E.K. built the electron-beam experimental setup with contributions from J.B., A.M., J.S., Y.Ya., I.K., and M.S.; N.Ri. performed energy loss calculations; C.R.-C. performed absorption map calculations; A.G. performed DFT calculations; C.R.-C. wrote code for optimizing nanophotonic scintillators with inputs from N.Ri., Z.L., and S.G.J.; Y.Yu and C.R.-C. fabricated the x-ray scintillation sample; and J.D.J., I.K., S.G.J., and M.S. supervised the project. The manuscript was written by C.R.-C. and N.Ri. with inputs from all authors. Competing interests: The authors declare the following potential competing financial interests: C.R.-C., N.Ri., A.G., S.E.K., Y.Ya., Z.L., J.B., N.Ro., J.D.J., I.K., S.G.J., and M.S. are seeking patent protection for ideas in this work (provisional patent application no. 63/178,176). C.R.-C., N.Ri., Z.L., and M.S. are seeking patent protection for ideas in this work (provisional patent application no. 63/257,611). Data and materials availability: The data and codes that support the plots within this paper and other findings of this study are available online (60). SUPPLEMENTARY MATERIALS

science.org/doi/10.1126/science.abm9293 Materials and Methods Supplementary Text Figs. S1 to S19 Table S1 References (61–82) 21 October 2021; accepted 22 December 2021 10.1126/science.abm9293

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RESEARCH ARTICLE SUMMARY

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Hyperexcitable arousal circuits drive sleep instability during aging Shi-Bin Li†, Valentina Martinez Damonte†, Chong Chen, Gordon X. Wang, Justus M. Kebschull, Hiroshi Yamaguchi, Wen-Jie Bian, Carolin Purmann, Reenal Pattni, Alexander Eckehart Urban, Philippe Mourrain, Julie A. Kauer, Grégory Scherrer, Luis de Lecea*

INTRODUCTION: Sleep destabilization is strongly

associated with aging and cognitive function decline. Despite sleep fragmentation being central to the most prevalent complaints of sleep problems in elderly populations, the mechanistic underpinnings of sleep instability remain elusive. Fragmented sleep during aging has been observed across species, indicating conserved underlying mechanisms across the phylogenetic tree. Therefore, understanding why the aging brain fails to consolidate sleep may shed light on translational applications for improving the sleep quality of aged individuals. RATIONALE: We hypothesized that the decline in sleep quality could be due to malfunction of the neural circuits associated with sleep/wake control. It has been established that hypocretin/

orexin (Hcrt/OX) neuronal activity is tightly associated with wakefulness and initiates and maintains the wake state. In this study, we investigated whether the intrinsic excitability of Hcrt neurons is altered, leading to a destabilized control of sleep/wake states during aging. RESULTS: Aged mice exhibited sleep fragmentation and a significant loss of Hcrt neurons. Hcrt neurons manifested a more frequent firing pattern, driving wake bouts and disrupting sleep continuity in aged mice. Aged Hcrt neurons were capable of eliciting more prolonged wake bouts upon optogenetic stimulations. These results suggested that hyperexcitability of Hcrt neurons emerges with age. Patch clamp recording in genetically identified Hcrt neurons revealed distinct intrinsic properties between

Aging Hcrt neuron

Hcrt neuron

Wake

CONCLUSION: Our data indicate that emerging hyperexcitability of arousal-promoting Hcrt neurons is strongly associated with fragmented sleep in aged mice, which display a lowered sleep-to-wake transition threshold defined for Hcrt neuronal activity. We have demonstrated that the down-regulation of KCNQ2/3 channels compromising repolarization drives Hcrt neuronal hyperexcitability, which leads to sleep instability during aging. Pharmacological remedy of sleep continuity through targeting KCNQ2/3 channels in aged mice confers a potential translational therapy strategy for improving sleep quality in aged individuals.

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Hyperexcitable Hcrt neurons drive sleep instability during aging. Elevated excitability of Hcrt neurons with depolarized RMPs and adaptive up-regulation of prepro-Hcrt mRNA expression converge to drive sleep/ wake instability in the aged brain with substantial Hcrt neuron loss. Hyperexcitable aged Hcrt neurons express functional impairment of KCNQ2/3 channelÐmediated M-current and an anatomical loss of KCNQ2, compromising the neurons to repolarize. 838

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the young and aged groups. Aged Hcrt neurons were hyperexcitable with depolarized membrane potentials (RMPs) and a smaller difference between RMP and the firing threshold. Aged Hcrt neurons expressing ChR2-eYFP were more sensitive to optogenetic stimulations, with a smaller-amplitude attenuation upon repetitive light pulse stimulations. More spikelets were generated in aged Hcrt neurons upon current injections. Recording from non-Hcrt neurons postsynaptic to Hcrt neurons revealed that optogenetic stimulation of Hcrt neurons expressing ChR2-eYFP reliably evoked timelocked postsynaptic currents (PSCs) after optogenetic stimulation more often in the aged group. Aged Hcrt neurons were characterized with a functional impairment of repolarizing M-current mediated by KCNQ2/3 channels and an anatomical loss of KCNQ2, revealed with array tomography at ultrastructural resolution. Single-nucleus RNA-sequencing (snRNAseq) revealed molecular adaptions, including up-regulated prepro-Hcrt mRNA expression and a smaller fraction of Kcnq family subtypes Kcnq1/2/3/5 in aged Hcrt neurons. CRISPR/ SaCas9–mediated disruption of Kcnq2/3 genes selectively in Hcrt neurons was sufficient to recapitulate the aging-associated sleep fragmentation trait in young mice. Pharmacological augmentation of M-current repolarized the RMP, suppressed spontaneous firing activity in aged Hcrt neurons, and consolidated sleep stability in aged mice. Sleep fragmentation in a narcolepsy mouse model with genetic ablation of Hcrt neurons at young ages manifested a mechanism other than hyperexcitable arousalpromoting Hcrt neurons that drives sleep fragmentation during healthy aging.

The list of author affiliations is available in the full article online. *Corresponding author. Email: [email protected] †These authors contributed equally to this work. Cite this article as S.-B. Li et al., Science 375, eabh3021 (2022). DOI: 10.1126/science.abh3021

READ THE FULL ARTICLE AT https://doi.org/10.1126/science.abh3021 science.org SCIENCE

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RESEARCH ARTICLE

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NEUROSCIENCE

Hyperexcitable arousal circuits drive sleep instability during aging Shi-Bin Li1,2†, Valentina Martinez Damonte1,2†, Chong Chen3,4, Gordon X. Wang1, Justus M. Kebschull5‡, Hiroshi Yamaguchi1,2§, Wen-Jie Bian1,2, Carolin Purmann1,6, Reenal Pattni1,6, Alexander Eckehart Urban1,6, Philippe Mourrain1,7, Julie A. Kauer1,2, Grégory Scherrer3,4, Luis de Lecea1,2* Sleep quality declines with age; however, the underlying mechanisms remain elusive. We found that hyperexcitable hypocretin/orexin (Hcrt/OX) neurons drive sleep fragmentation during aging. In aged mice, Hcrt neurons exhibited more frequent neuronal activity epochs driving wake bouts, and optogenetic activation of Hcrt neurons elicited more prolonged wakefulness. Aged Hcrt neurons showed hyperexcitability with lower KCNQ2 expression and impaired M-current, mediated by KCNQ2/3 channels. Single-nucleus RNA-sequencing revealed adaptive changes to Hcrt neuron loss in the aging brain. Disruption of Kcnq2/3 genes in Hcrt neurons of young mice destabilized sleep, mimicking agingassociated sleep fragmentation, whereas the KCNQ-selective activator flupirtine hyperpolarized Hcrt neurons and rejuvenated sleep architecture in aged mice. Our findings demonstrate a mechanism underlying sleep instability during aging and a strategy to improve sleep continuity.

S

leep quality correlates with cognitive function (1, 2), and decline in sleep quality is among the most prevalent complaints during aging in humans (3, 4). Aging is associated with alterations in sleep architecture, prominently sleep fragmentation, which prevents restorative sleep (3, 5). The ability to sustain sleep/wake states during aging is heavily impaired across species (5–7), suggesting that the underlying mechanisms are conserved across the phylogenetic tree. However, the cellular and molecular underpinnings of sleep instability during aging are unknown. A plausible mechanism underlying aging-related sleep fragmentation is that elevated intrinsic excitability of arousal-promoting circuits emerges with age, disrupting sleep stability. Hypocretin/orexin (Hcrt/OX) neurons (8, 9) in the lateral hypothalamus (LH) play a pivotal role in sleep/wake control (10, 11). Optogenetic stimulation of Hcrt neurons during sleep triggers sleep-to-wake transition (12, 13), whereas optogenetic suppression of Hcrt neuronal acti-

1

Department of Psychiatry and Behavioral Sciences, Stanford University School of Medicine, 1201 Welch Road, Stanford, CA 94305, USA. 2Wu Tsai Neurosciences Institute, Stanford University, Stanford, CA 94305, USA. 3Department of Cell Biology and Physiology, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA. 4UNC Neuroscience Center, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA. 5Department of Biology, Stanford University, Stanford, CA 94305, USA. 6Department of Genetics, Stanford University School of Medicine, Stanford, CA 94305, USA. 7 INSERM 1024, Ecole Normale Supérieure, Paris, France. *Corresponding author. Email: [email protected] †These authors contributed equally to this work. ‡Present address: Department of Biomedical Engineering, Johns Hopkins University, Baltimore, MD 21205, USA. §Present address: Department of Neuroscience II, Research Institute of Environmental Medicine, Nagoya University, Nagoya 464-8601, Japan.

Li et al., Science 375, eabh3021 (2022)

vity induces non–rapid eye movement (NREM) sleep (14). Furthermore, genetic Hcrt neuron depletion (15) or Hcrt receptor 2 (HcrtR2) mutation (16) leads to narcolepsy with cataplexy, a condition in which patients suffer sleep and wake fragmentation (17). In vivo electrophysiological recordings demonstrate that Hcrt neuronal activity is correlated with wakefulness and initiates and maintains wake state (18, 19). We thus hypothesized that emerging hyperexcitability of Hcrt neurons drives sleep instability during aging. Results Aged mice exhibit fragmented sleep and significant loss of Hcrt neurons

We compared the sleep/wake patterns between young (3 to 5 months) and aged (18 to 22 months) wild-type (WT) mice implanted with electroencephalogram (EEG)–electromyography (EMG) electrodes. Wake and NREM but not REM sleep were more fragmented in aged mice (fig. S1). We next determined the number of Hcrt neurons in these mice and found a significant loss (~38%) of Hcrt neurons in aged mice compared with young mice (fig. S2), indicating a high vulnerability of these neurons in the aging brain. Fragmented sleep pattern with increased Hcrt neuronal activity in aged mice

We monitored the intrinsic activity of Hcrt neurons using fiber photometry recording of GCaMP6f signals in both young and aged Hcrt::Cre mice (20) while simultaneously recording EEG-EMG signals (Fig. 1) during the light phase, when mice exhibited a stable sleep/ wake pattern (fig. S1). We found scattered Hcrt

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neuronal GCaMP6f transients during sleep (GS) and GCaMP6f epochs associated with wakefulness (GW) in both young and aged mice. The GCaMP6f amplitude change (Z score) was smaller in the aged group (Fig. 1, C and D), indicating that the threshold of Hcrt neuronal activity that defines sleep-to-wake transition is lower in aged mice. The frequency of GW was significantly higher in aged mice (young, 16.1 ± 0.7 counts/hour versus aged, 22.8 ± 1.4 counts/ hour) (Fig. 1D, bottom right). The GW epoch frequencies of Hcrt neurons matched the wake bout counts recorded during the same time window in young and aged WT mice, respectively (fig. S1B). The peak and duration of both GS (Fig. 1C, middle right) and GW (Fig. 1D, middle right) were smaller in aged mice. In the same amount of recording time during the same circadian phase, the mean bout duration of sleep, wake, and sleep-wake (S-W) episodes was shorter in aged mice (Fig. 1E); a fragmented sleep/wake pattern was associated with age. Correlation analysis with a linear fit revealed that sleep bout duration negatively correlates with Hcrt GW epoch frequency (Fig. 1F), suggesting the possibility that sleep bout shortening is driven by Hcrt neuron hyperactivity. Longer wakefulness upon optogenetic activation of aged Hcrt neurons

We then injected adeno-associated virus (AAV) vectors encoding ChR2–enhanced yellow fluorescent protein (eYFP) in the LH of young (3 to 5 months) and aged (18 to 22 months) Hcrt:: Cre mice (fig. S3, A and B) and implanted fiber optics and EEG-EMG electrodes. After recovery with sufficient virus expression, we stimulated Hcrt neurons in both young and aged mice with a range of blue light intensities (1, 5, 10, 15, and 20 mW) and frequencies (1, 5, 10, 15, and 20 Hz) within 30 s from either NREM onset (Fig. 2, A to F, and fig. S3) or REM sleep onset (Fig. 2, G to L, and fig. S3). Stimulation with high light intensities and frequencies elicited immediate NREM/REM sleep-to-wake transitions in both young and aged mice (Fig. 2, A and G). The sleep-to-wake transition latency is generally shorter in aged mice according to condition-matched comparison (Fig. 2, B and H) and data aggregated for individual mouse (Fig. 2, C and I). Activation of Hcrt neurons evoked significantly longer durations of wakefulness in aged mice as revealed by comparisons based on each stimulation condition (Fig. 2, E and K) and data aggregated for the individual mouse (Fig. 2, F and L) for optogenetic stimulation during either NREM (young, 162.7 ± 5.4 s versus aged, 292.0 ± 8.3 s) (Fig. 2F) or REM sleep (young, 69.0 ± 3.5 s versus aged, 134.0 ± 2.5 s) (Fig. 2L). The surface plots of in vivo optogenetic data demonstrated that compared with the aged mice, the young mice required stronger stimulation to elicit wake bouts with identical lengths, as 1 of 14

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Fig. 1. Spontaneous activity of Hcrt neurons across sleep/wake states in young and aged mice. (A and B) Representative EEG, EEG power spectra, EMG, simultaneous Hcrt GCaMP6f signals from (A) young and (B) aged mice. The arrows indicate GCaMP6f transients during sleep (GS), and the black triangles indicate GCaMP6f epochs associated with wakefulness (GW). (C) Staged GS signals during 10 s around the start of GS transients from identical length (6 hours, 1 hour/mouse) of recorded GCaMP6f signals from young and aged mice (n = 6 mice each group), respectively, during light phase, averaged trace plot (right top), scatter plot of individual GS duration against GS peak (young, n = 128; aged, n = 171) (right middle), animal-based comparison of GS signals for Z score and GS frequency (right bottom). (D) Staged GW signals during 10 s

indicated by the cutaway surface (Fig. 2, D and J) for the mean value of wake duration in aged mice (Fig. 2, F and L). These results demonstrate that the threshold of Hcrt neuronal activity defining the sleep-to-wake transition was lower in aged mice, which is consistent with the hypothesis that aged Hcrt neurons are hyperexcitable. Elevated intrinsic excitability of aged Hcrt neurons

To determine directly whether the intrinsic excitability of Hcrt neurons differs with age, we recorded spontaneous neuronal activity from ChR2-eYFP–labeled Hcrt neurons with wholeLi et al., Science 375, eabh3021 (2022)

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110 60 10 15 20 25 30 210 Aged (A) R2 = 0.7025 *P = 0.0372 160 110 60 10 15 20 25 30 210 Y-A pooled 2 R = 0.6516 160 ***P = 0.0015 110 60 10

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around start of GW epochs from identical length (6 hours, 1 hour/mouse) of recorded GCaMP6f signals from young and aged mice, averaged trace plot (right top), scatter plot of individual GW duration against GW peak (young, n = 102; aged, n = 137) (right middle), animal-based comparison of GW signals for Z score and GW frequency (right bottom). (E) Animal-based comparison of mean bout duration for sleep, wake, and entire S-W episodes (n = 6 mice each group). (F) Correlation for mean sleep bout duration against GW bout counts/hour in young, aged, and pooled datasets. Data represent mean ± SEM. In (C) to (E) unpaired t test with Welch’s correction; (F), Spearman correlation, linear fit and 95% confidence band; *P < 0.05, **P < 0.01, ***P < 0.005, ****P < 0.001, †P < 0.0005; statistical details see supplementary text.

cell patch clamp recording in brain slices from young and aged Hcrt::Cre mice (Fig. 3). Immunostaining against Hcrt1 confirmed that the recorded neurons infused with biocytin were Hcrt1-positive (Fig. 3A). A higher fraction of aged versus young Hcrt neurons exhibited spontaneous firing (young, 12 of 33 versus aged, 9 of 21) (Fig. 3B). Despite comparable input resistances between young and aged Hcrt neurons (Fig. 3D), the resting membrane potential (RMP) of aged Hcrt neurons was more depolarized than young Hcrt neurons (young, –60.5 ± 1.9 mV versus aged, –51.5 ± 3.1 mV) (Fig. 3E). Ion channels that determine the firing threshold remained unchanged with

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age because the most negative voltage that must be reached for all-or-none firing to occur (21) was comparable between young and aged Hcrt neurons (young, –34.2 ± 1.6 mV versus aged, –36.3 ± 1.8 mV) (Fig. 3F). The difference between RMP and firing threshold was smaller in aged Hcrt neurons (young, 19.8 ± 2.6 mV versus aged, 11.4 ± 1.5 mV) (Fig. 3G), priming aged Hcrt neurons to fire action potentials (APs) after smaller depolarizations. Young Hcrt neurons also exhibited higher-amplitude APs than those of aged Hcrt neurons (young, 56.2 ± 5.2 mV versus aged, 42.3 ± 1.8 mV) (Fig. 3, B, C and H), although other AP properties did not significantly differ (Fig. 3, I to L). 2 of 14

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Impaired M-current with loss of KCNQ2 channels in aged Hcrt neurons

Hyperexcitability in aged Hcrt neurons with depolarized RMPs suggested a change in ionic conductance such as K+ conductance mediated by voltage-gated potassium channels (KCNQ). Li et al., Science 375, eabh3021 (2022)

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Fig. 2. More prolonged wake bouts upon optogenetic stimulation of Hcrt neurons expressing ChR2-eYFP in aged mice. (A) Surface plot of NREM-towake transition latency based on the mean value of each stimulation condition. (B and C) Comparison of NREM-to-wake transition latency based on (B) each stimulation condition and (C) the mean value for each animal. (D) Surface plot of wake duration based on the mean value of each stimulation condition. The cyan cutaway surface indicates the mean value for the aged group. (E and F) Comparison of wake duration based on (E) each stimulation condition and (F) the mean value for each animal. (G) Surface plot

We next compared light-evoked firing activity between the young and aged Hcrt neurons expressing ChR2-eYFP. We tested different stimulation frequencies and compared the response attenuation, which is defined as the amplitude difference between the first and last light pulse–evoked responses after a train of blue light stimulations. The response attenuation was significantly smaller in aged Hcrt neurons than in young Hcrt neurons (Fig. 3, M and N). Recordings from non-Hcrt neurons postsynaptic to Hcrt neurons (fig. S4A) demonstrated that optogenetic stimulation of Hcrt neurons expressing ChR2-eYFP reliably evoked time-locked postsynaptic currents (PSCs) after optogenetic stimulation more often in the aged group than in the young group (young, 3 of 15 versus aged, 6 of 18) (fig. S4B). More neurons in slices from young mice exhibited PSC failures compared with those from aged mice (fig. S4, C and D). To test whether differences in excitability could be attributed to differential expression of ChR2-eYFP, we performed step-current injection in both young and aged Hcrt neurons. More spikelets were evoked in aged Hcrt neurons by the same current injection protocol (Fig. 3, O and P), again indicating hyperexcitability of aged Hcrt neurons.

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of REM-to-wake transition latency based on the mean value of each stimulation condition. (H and I) Comparison of REM-to-wake transition latency based on (H) each stimulation condition and (I) the mean value for each animal. (J) Surface plot of wake duration based on the mean value of each stimulation condition. The cyan cutaway surface indicates the mean value for the aged group. (K and L) Comparison of wake duration based on (K) each stimulation condition and (L) the mean value for each animal. In (B), (C), (E), (F), (H), (I), (K), and (L): Mann-Whitney U test; ***P < 0.005, P < 0.0005. Statistical details are available in the supplementary text.

There are five mammalian subtypes named KCNQ1 to -5 (Kv7.1 to Kv7.5) (22, 23), and KCNQ2 pairs with the KCNQ3 subunit to form KCNQ2/3 heterotetramers, constituting primarily the molecular substrate of the M-current (IM) (24), which plays a critical role in governing neuronal subthreshold excitability, repolarization, and sensitivity to synaptic inputs (23–25). To test this idea, we applied KCNQ2/3 channelselective modulators to Hcrt neurons expressing eYFP in brain slices from either young or aged mice (Fig. 4, A-F). Perfusion of a KCNQ2/3selective blocker, XE991 (50 mM), significantly depolarized the RMP and increased the firing frequency in young Hcrt neurons (Fig. 4, A to C). Reciprocally, application of a KCNQ2/3selective activator, flupirtine (50 mM), hyperpolarized the RMP and reduced the firing frequency in aged Hcrt neurons (Fig. 4, D to F). XE991 reduced IM in young Hcrt neurons (before, –11.2 ± 1.3 pA versus after, –5.2 ± 0.8 pA) (Fig. 4G, top). Conversely, flupirtine increased IM in both young (before, –16.9 ± 3.8 pA versus after, –22.6 ± 5.2 pA) (Fig. 4G, bottom) and aged (before, –14.6 ± 1.1 pA versus after: –18.0 ± 1.5 pA) (Fig. 4H, bottom) Hcrt neurons. The basal IM in aged Hcrt neurons was significantly smaller than in young Hcrt neurons (young, –17.1 ± 1.9 pA versus aged, –11.8 ± 1.2 pA) (Fig. 4I). These results were validated with array tomography at ultrastructural resolution (26), which revealed a significant reduction in KCNQ2 immunoreactivity in aged Hcrt neurons (Fig. 4J). To determine the extent of differences between young and aged Hcrt neurons at the

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RES EARCH | R E S E A R C H A R T I C L E

transcriptomic level, we performed singlenucleus RNA-sequencing (snRNA-seq). Aged Hcrt neurons developed adaptive up-regulation of prepro-Hcrt mRNA expression in both male (fig. S5) and female (fig. S6) mice, suggesting potential compensatory syntheses of Hcrt neuropeptides by individual Hcrt neurons. Although the normalized expression level of Kcnq subtypes was not significantly different between the young and aged groups, the percentage of aged Hcrt neurons actively expressing Kcnq1/2/ 3/5 mRNAs, the dominant subtypes, was lower (figs. S5E and S6E) and expected to contribute to the hyperexcitability of aged Hcrt neurons. CRISPR/SaCas9Ðmediated disruption of Kcnq2/3 genes in young Hcrt neurons destabilizes NREM sleep

Given the broad expression of KCNQ channels in the brain (25), what is the contribution of IM in Hcrt neurons to the overall sleep architecture? To answer this question, we used CRISPR/SaCas9–mediated disruption (27) of Kcnq2/3 genes specifically in Hcrt neurons in young mice to mirror the impaired IM observed in aged Hcrt neurons. We designed AAV vectors for Cre-dependent expression of SaCas9 (28), sgControl, and sgKcnq2/3 targeting Kcnq2/3 genes in Hcrt neurons (Fig. 5). Young Hcrt::Cre mice from different litters were randomly separated into two groups. We delivered a viral mixture of SaCas9 and sgControl to the Hcrt field bilaterally in the control group, whereas the other group received bilateral injection of a SaCas9 and 3 of 14

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Fig. 3. Hyperexcitability in aged Hcrt neurons revealed with whole-cell patch clamp recording. (A) Representative slices containing recorded ChR2eYFP–labeled Hcrt neurons infused with biocytin. (B) Representative traces and fractions of young and aged Hcrt neurons with and without spontaneous firing activities. (C) Averaged traces of spontaneous APs shown in (B). (D to L) Comparison of basic electrophysiological properties between young and aged Hcrt neurons. (D) Input resistance and (E) RMP of all the recorded young and aged Hcrt neurons (young, n = 33 neurons versus aged, n = 21 neurons from eight mice each group). Comparison of other parameters including (F) firing threshold, (G) difference between RMP and firing threshold, (H) AP peak amplitude, (I) AP rising time, (J) AP half duration, (K) maximum rising slope, and (L) decaying slope of spontaneous APs between young and aged Hcrt neurons (young, n = 12 neurons versus aged, n = 9 neurons from eight mice each group).

sgKcnq2/3 viral mixture for disruption of Kcnq2/3 genes (Fig. 5A). All the mice were implanted with EEG-EMG electrodes for sleep/ wake pattern monitoring for a 2-day consecutive recording of EEG-EMG signals weekly for 8 weeks. CRISPR/SaCas9–mediated deactivation of Kcnq2/3 genes in Hcrt neurons was sufficient to generate NREM sleep fragmentation in young mice (NREM mean bout length at 8 weeks after virus injection, 48 hours; sgControl, 2.1 ± 0.04 min versus sgKcnq2/3, 1.7 ± 0.1 min; light phase, sgControl, 2.2 ± 0.1 min versus sgKcnq2/3, 1.9 ± 0.1 min; dark phase, sgControl, 2.0 ± 0.1 min versus sgKcnq2/3, 1.6 ± 0.1 min) (Fig. 5B). We then performed whole-cell recording from individual mCherry-labeled Hcrt neurons (Fig. 5C) after EEG-EMG recording at 8 weeks after virus injection and found that the Hcrt neurons with Kcnq2/3 gene disruptions showed a depolarized RMP (sgControl, –67.0 ± Li et al., Science 375, eabh3021 (2022)

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(M) (Top) Representative traces of young and aged Hcrt neurons expressing ChR2-eYFP upon optogenetic stimulation. (Bottom) The same responses on a slower time base, illustrating the response to the first and last light pulse stimulations at each stimulation frequency (membrane voltage/Vm). (N) Significant reduction of response attenuation calculated based on the first and the last response from trains as in M (young, n = 23 neurons versus aged, n = 21 neurons from eight mice each group). (O and P) Step current injections triggered more spikelets in aged Hcrt neurons than in young Hcrt neurons [(O) young, n = 33 neurons versus aged, n = 26 neurons from eight mice each group; (P) representative traces and current injection protocol]. In (D) to (L): Mann-Whitney U test; (N) and (O): two-way ANOVA followed by post hoc Šidák’s multiple comparisons; *P < 0.05, **P < 0.01, †P < 0.0005. Statistical details are available in the supplementary text.

2.4 mV versus sgKcnq2/3, –55.9 ± 3.3 mV) (Fig. 5D) and spontaneous firing activity in higher proportion (Fig. 5E), mimicking the aged Hcrt neurons. EEG-EMG recording up to 12 weeks after virus infection in a subset of these mice (fig. S7) further validated our observations at 8 weeks after virus injection. Analyses of the basic electrophysiological properties of the spontaneous APs revealed that artificial disruption of KCNQ2/3 channels in young Hcrt neurons (fig. S7, E and F) mimicked some features observed in the aged Hcrt neurons, including a trend of reduction in the maximum rising/decaying slope of spontaneous APs (Fig. 3, D to L). In vivo evaluation of KCNQ2/3-selective ligands

To further test the role of KCNQ2/3 channels in sleep modulation, we administered (intraperitoneally) either the KCNQ2/3-selective blocker XE991 (2 mg/kg) or the saline vehicle as control

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to young (3 to 5 months) WT mice at the beginning of the light phase, when there is a strong sleep pressure. XE991 significantly increased the wake amount during the first hour after injection compared with that of the control group (Fig. 6A) without affecting the power spectra (Fig. 6, C, E, and G). Reciprocally, we injected the KCNQ2/3–selective activator, flupirtine (intraperitoneally, 20 mg/kg) or 0.3% dimethyl sulfoxide (DMSO) in saline (v/v) as vehicle to aged (18 to 22 months) WT mice at the beginning of the light phase. Flupirtine significantly increased the amount and stability of NREM sleep compared with the control group (Fig. 6B). Flupirtine also increased the theta band power during NREM sleep and the initial REM sleep segment after drug administration (Fig. 6, D, F and H). Sleep quality is correlated with cognitive functions (1, 2), and flupirtine administered to aged mice at the 4 of 14

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Fig. 4. Impaired IM associated with loss of KCNQ2 in aged Hcrt neurons. (A) Representative traces from a young Hcrt neuron (left) before or (right) in the presence of a KCNQ2/3 blocker XE991 (50 mM). (B) XE991 depolarized RMP and (C) increased firing frequency in young Hcrt neurons (n = 19 neurons from seven mice). (D) Representative traces from an aged Hcrt neuron (left) before or (right) in the presence of a KCNQ2/3 activator flupirtine (50 mM). (E) Flupirtine hyperpolarized RMP and (F) decreased firing frequency in aged Hcrt neurons (n = 8 neurons from five mice). (G) IM in young Hcrt neurons modulated by XE991 (top; n = 6 neurons from three mice) and flupirtine (bottom; n = 10

beginning of light phase after the familiarization session in the object-recognition task also improved the subsequent exploration of the new object (fig. S8). Sleep instability in a narcolepsy mouse model with genetic ablation of Hcrt neurons

Abrupt Hcrt neuron loss in pathological conditions at young ages causes type I narcolepsy, a condition characterized by excessive daytime sleepiness and a sudden loss of muscle tone with EEG pattern resembling REM sleep, known as cataplexy, as well as sleep fragmentation (17). We crossed OX(Hcrt)–enhanced green fluorescent protein (eGFP) mice (29) with OX(Hcrt)-ataxin3 mice, a narcolepsy mouse model (15), to generate mice with Hcrt neurons Li et al., Science 375, eabh3021 (2022)

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neurons from five mice). (H) IM in aged Hcrt neurons modulated by XE991 (top; n = 7 neurons from three mice) and flupirtine (bottom; n = 15 neurons from five mice). (I) Basal IM in young Hcrt neurons (n = 25 neurons from nine mice) versus in aged Hcrt neurons (n = 26 neurons from nine mice). (J) Array tomography revealed reduced KCNQ2 expression in aged Hcrt neurons (n = 4 mice/group). In (B) and (C), Wilcoxon matched-pairs signed rank test; (E) and (F), RM one-way ANOVA followed by post hoc Tukey’s multiple comparisons; (G), (H), and (J), paired t test; (I) unpaired t test with Welch’s correction; statistical details are available in the supplementary text.

that express both eGFP and ataxin3, allowing us to examine the activity of these neurons while monitoring EEG-EMG patterns of their littermates (figs. S9 and S10). EEG-EMG recording from 5-week-old mice expressing ataxin3 exhibited mild NREM sleep fragmentation, with three of six mice showing cataplexy-like EEGEMG epochs compared with their control group with intact Hcrt neurons (fig. S9, A to C), according to established criteria (30). In recordings from brain slices, although Hcrt cells from the ataxin3-expressing group had a more depolarized RMP—a smaller difference between RMP and firing threshold—as well as a higher fraction of spontaneously firing neurons compared with that of age-matched controls, other basic electrophysiological prop-

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erties were similar (fig. S9, D to G). Ataxin3expressing mice at an age of 12 weeks showed obvious NREM sleep fragmentation with a severe cataplexy-like EEG-EMG pattern (six of six mice) (fig. S10A). Immunostaining against Hcrt1 showed a near complete Hcrt neuron degeneration at the age of 12 weeks in mice expressing ataxin3 (fig. S10B), confirming Hcrt neuron loss around a similar age in this narcolepsy mouse model (15). Thus, although both healthy aged WT mice and young mice expressing ataxin3 show sleep fragmentation, the underlying mechanisms are not identical. Discussion

Sleep quality decline—in particular, fragmented nocturnal sleep during aging—impairs daytime 5 of 14

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Fig. 5. CRISPR/SaCas9Ðmediated disruption of Kcnq2/3 genes in Hcrt neurons leads to NREM sleep fragmentation in young mice. (A) Schematic of AAV sgControl, AAV SaCas9, AAV sgKcnq2/3 vector design, and bilateral viral infection of Hcrt neurons in young Hcrt::Cre mice. (B) Two-hour (left) binned percentage, (middle left) bout counts, (middle right) mean bout length and (right) mean bout length based on circadian phase for wake, NREM, and REM sleep at 1 week (top) and 8 weeks (bottom) after injection of a virus mixture, as illustrated in (A) (n = 10 mice/group, dark phase indicated by gray shielding). (C) Representative slices expressing sgRNA with fluorescent mCherry flag and

well-being in elderly individuals (3). However, the mechanistic underpinnings of aging-related sleep fragmentation are unknown. In this study, we report a mechanism underlying sleep instability during aging. We found a generally fragmented sleep/wake pattern in aged mice with reduced wakefulness during their active phase (fig. S1), replicating the sleep traits in aged populations (3). We further observed more frequent Hcrt GCaMP6f activity epochs driving the sleep fragmentation in aged mice (Fig. 1). Despite a reduction in the number of wakepromoting Hcrt neurons in aged mice (fig. S2), these mice paradoxically manifested significantly longer wake bouts in response to Hcrt neuron optogenetic stimulation (Fig. 2 and fig. S3). Immunostaining against Hcrt1 confirmed that the majority of the virus-infected neurons are hypocretinergic (fig. S3, B and C), and the small fraction of non-Hcrt neurons may be assigned to the ~30 cell types described in the LH (31), none of which are likely to affect bout length directly (32–34). Aged Hcrt neurons exhibited increased intrinsic excitability, with more depolarized RMPs (Fig. 3), more spikelets per unit current (Fig. 3, O and P), and upLi et al., Science 375, eabh3021 (2022)

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SaCas9-3HA for sgControl and sgKcnq2/3 group, respectively. Patch clamp recorded cells were labeled with biocytin, and post hoc antibody staining against HA tag confirmed the cells expressing SaCas9 for data analyses. (D) Comparison of RMPs between sgControl and sgKcnq2/3 group (n = 14 neurons from three mice each group). (E) Fractions of neurons with different firing frequencies in the (left) sgControl and (right) sgKcnq2/3 groups. Data indicate mean ± SEM [(B) left to middle right, two-way RM ANOVA followed by Šidák’s multiple comparisons; (B) right, Holm-Šidák; (D) Mann-Whitney U test; *P < 0.05, ***P < 0.005, †P < 0.0005; statistical details are avialable in the supplementary text].

regulated prepro-Hcrt nuclear mRNA expression (figs. S5 and S6). To understand the molecular mechanisms underlying the phenotypes described above, we focused on the ion channels that regulate the intrinsic excitability of neurons. Potassium channels play an important role in governing the excitability of neurons through repolarizing action potentials (22, 25). Specifically, KCNQ2/3 channels are expressed broadly in brain regions controlling neuronal network oscillations and synchronization (35), and a moderate loss of function of these channels causes epilepsy in humans (36, 37) and mice (38). In aged Hcrt neurons, we discovered impaired KCNQ2/3–mediated IM associated with lower KCNQ2 channel density (Fig. 4, I and J). The loss of KCNQ2 may be due to oxidation, a known factor for potassium conductance impairment during aging (39). Decreased levels of transcription factor specificity protein 1 (sp1) in senescent cells (40) might be another reason for impaired IM in aged Hcrt neurons because sp1 has been shown to activate the expression of KCNQ2/3 and augment IM (41). Our data support the hypothesis that the arousal

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circuitry, and particularly the Hcrt system, becomes hyperexcitable during aging. Selective disruption of Kcnq2/3 genes in young Hcrt neurons was sufficient to depolarize these neurons and cause sleep fragmentation (Fig. 5 and fig. S7), mimicking the sleep instability observed in aged mice (fig. S1). Further advancing these findings, systemic administration of a KCNQ2/3 blocker increased wakefulness (Fig. 6A), whereas a KCNQ2/3 activator consolidated NREM sleep (Fig. 6B). Specifically targeting the Hcrt system with a pharmacological tool, application of a dual Hcrt/OX receptor antagonist MK6096 (filorexant, 20 mg/kg, intraperitoneally) also increased the amount of NREM sleep and mean NREM bout length within 6 hours after drug administration (fig. S11). Our pharmacological data may open a new approach for conquering sleep quality decline during aging. On the basis of our scRNA-seq data (figs. S5 and S6), KCNQ1/5 mRNA are expressed in Hcrt neurons and are expected to have a lower KCNQ subunit expression level in aged Hcrt neurons both in male (fig. S5E) and female mice (fig. S6E). Factors other than impaired 6 of 14

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hypocretinergic tone in AD mouse models (43). Ab reduces gene expression of Kcnq2/3 and Girk2/3/4 in hippocampal slices incubated with Ab fragment Ab25-35 (44) in line with a deleterious cycle of hyperactivation, with multiple excitatory elements implicating Abinduced hyperexcitation in hippocampal neurons (45), which links AD pathology–mediated down-regulation of K+ channels to neuronal excitability. Loss of hyperexcitable arousalpromoting neurons destabilizing sleep during aging could be drastically exacerbated by AD pathology, as evidenced by a study of post

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Fig. 6. Pharmacological manipulation of sleep/wake states with KCNQ2/3 ligands. (A) Significantly increased wake amount by the KCNQ2/3 blocker XE991 (2 mg/kg) in young mice. (B) Significantly increased NREM amount and mean bout length by the KCNQ2/3 activator flupirtine (20 mg/kg) in aged mice. (C) Representative EMG-EEG raw traces from vehicle- and XE991-treated (2 mg/kg) young mice. (D) Representative EMG-EEG raw traces from vehicle- and flupirtine-treated (20 mg/kg) aged mice. (E) Power spectra of EEG for vehicle- and XE991-treated young mice and (F) power spectra of

M-current with a key role in neuron repolarization may also contribute to increased excitability of arousal-promoting circuits during aging. Together with KCNQ family, G protein– gated inward rectifying K+ channels (Girks) are expressed in the brain and mediate outward potassium current in hyperpolarizing neurons and decreasing intrinsic excitability (42). Our findings in aged animals may extend to neurodegenerative conditions such as Alzheimer’s disease (AD). The level of amyloid-b (Ab, a marker of AD) in brain interstitial fluid correlates with wakefulness and increases with elevated

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mortem brains from AD patients that demonstrate a ~32% Hcrt neuron loss compared with their age-matched controls without AD (46). Among the main downstream targets of Hcrt neurons (47, 48), locus coeruleus noradrenergic (LC NA) neurons displayed a milder cell count loss (~15%) (fig. S12) compared with Hcrt neuron loss (~38%) (fig. S2) in the same group of aged mice. Optogenetic activation of LC NA neurons elicited sleep-to-wake transitions and maintained wakefulness more robustly, as indicated by shorter sleep-towake transition latencies and longer wake bout 7 of 14

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durations in aged mice with the same optogenetic stimulations in young and aged mice (fig. S13). Electrophysiological recordings revealed a more depolarized RMP and a higher proportion of neurons with spontaneous firing activity in aged LC NA neurons (fig. S14). These results suggested a potential up-regulation of excitability in other arousal-promoting brain nuclei during aging. Sleep instability and fragmentation not only appears in the elderly but also have been observed in type I narcolepsy patients with loss of Hcrt neurons at young ages, yet the pathology may develop gradually (17), which raises the question that whether the spontaneous activity of the remaining Hcrt neurons are up-regulated to compensate for the rapid Hcrt neuron loss in the narcolepsy pathological condition. With a narcolepsy mouse model, we found that the remaining Hcrt neurons exhibited depolarized RMPs and a higher fraction with spontaneous firing activity (fig. S9, D to G), despite other AP properties being similar to those of agematched controls around 5 weeks of age. Yet because the 12-week-old ataxin3+ mice have almost completely lost their Hcrt neurons, the even more fragmented sleep features in these mice (compared with the sleep pattern around 5 weeks) (figs. S9 and S10) cannot be attributed to alteration of Hcrt/OX neuronal excitability. Increased depolarization of the remaining Hcrt neurons in ataxin3-expressing mice may result from toxicity introduced by ataxin3 expression or neural circuit reorganization or malfunction during rapid Hcrt neuron loss, whereas elevated depolarization in aged mice is the result of an altered complement of membrane ion channels. Although it is possible that there is also neural circuit reorganization or malfunction accompanying chronic Hcrt neuron loss during natural healthy aging, the absence of a cataplexy-like EEGEMG pattern in healthy aged WT mice highlighted that the mechanisms underlying sleep fragmentation in young OX(Hcrt)-ataxin3 mice and healthy aged WT mice are not identical. Collectively, our study delineates that elevated Hcrt neuron excitability is associated with sleep fragmentation during aging. A lower threshold defining sleep-to-wake transitions driven by hyperexcitable Hcrt neurons accounts for sleep fragmentation and yields longer wake bouts upon optogenetic stimulation of these neurons in aged mice. The restoration of sleep stability in aged mice upon manipulation of KCNQ channels may lead to the development of potential therapeutic strategies in aged individuals whose sleep fragmentation contributes to aging-related neurodegeneration. Materials and methods Animals

Experiments with mice were performed following the protocols approved by the Stanford Li et al., Science 375, eabh3021 (2022)

University Animal Care and Use Committee in accordance with the National Institutes of Health Guide for the Care and Use of Laboratory Animals. Discomfort, distress, and pain were minimized with anesthesia and analgesic medications. Mice were housed in a temperature- and humidity-controlled animal facility with a 12-hours/12-hours light/dark cycle (9 am light on, Zeitgeber time 0/ZT 0), unless otherwise specified. Mice had ad libitum access to standard laboratory mouse food pellets and water. 2-3 month young male adult wild type (WT) mice were acquired from Jackson Laboratory (Jax) and 18 month old WT male mice were acquired from National Institute on Aging (NIA). OX(Hcrt)-ataxin3 heterozygotes (15), Hcrt-IRES-Cre knock-in (Hcrt::Cre) heterozygotes (20), OX(Hcrt)-eGFP heterozygotes (29) and tyrosine hydroxylase (TH)-IRES-Cre knock-in (TH::Cre) heterozygotes (European Mouse Mutant Archive; EMMA ID: EM:00254) (49) were backcrossed onto C57BL/6J background. Male mice were used in the experiments, unless otherwise specified. Mice at an age younger than 5 months belonged to the young group, whereas mice older than 18 months were considered as aged. Animals from multiple litters were randomly assigned to control or experimental group under each experimental paradigm. Group sizes were determined based on earlier publications (13, 50, 51). EEG-EMG electrode preparation and implantation

Mini-screw (US Micro Screw) was soldered to one tip of an insulated mini-wire with two tips exposed, and the other tip of the mini-wire was soldered to a golden pin aligned in an electrode socket. A micro-ring was made on one side of an insulated mini-wire with the other end soldered to a separate golden pin in the electrode socket. Each electrode socket contained 4 channels with 2 mini-screw channels for EEG recording and 2 micro-ring channels for EMG recording as described in earlier work from our lab (12, 47, 50). The resistance of all the channels was controlled with a digital Multimeter (Fluke) to be lower than 1.5 ohms for ideal conductance. Mice were mounted onto an animal stereotaxic frame (David Kopf Instruments) under anesthesia with intraperitoneal injection of a mixture of ketamine (100 mg/kg) and xylazine (20 mg/kg). Two mini-screws were placed in the skull above the frontal (AP: −2 mm; ML: ± 1 mm) and temporal (AP: 3 mm, ML: ± 2.5 mm) cortices for EEG signal sampling and two micro-rings were placed in the neck muscles for EMG signal acquisition. Electrode socket was secured with Metabond (Parkell, Japan) and dental acrylic on skull for recording in freely moving mice. Buprenorphine SR (0.5 mg/kg) was admin-

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istered subcutaneously to mice before and after surgery for pain relief. After surgery, revertidine (5 mg/kg) was administered (intraperitoneally) to mice to facilitate recovery from anesthesia. Virus injection with and without fiber optic implantation Optogenetic experiments

0.3 ml AAV-DJ-EF1a-DIO-hChR2(H134R)-eYFP viruses (ChR2-eYFP, 6.5 × 1012 gc/ml, Stanford Virus Core, Lot no. 4176) was delivered to LH (AP: −1.35 mm, ML: ± 0.95 mm, DV: −5.15 mm) of anesthetized young (3 to 5 months) or aged (18 to 22 months) Hcrt::Cre mice with a 5 ml Hamilton microsyringe according to stereotaxic coordinates determined on a Kopf stereotaxic frame. AAV-DJ-EF1a- DIO-eYFP viruses (eYFP, 6.9 × 1012 gc/ml, Stanford Virus Core, Lot no. 3010) was used as control or for in vitro pharmacology experiments. A glass fiber (200 mm core diameter, Doric Lenses, Franquet, Québec, Canada) was implanted with the tip right above the injection site for optogenetic stimulations later on. After fixing the glass fiber with Metabond, the EEG/EMG electrodes were implanted with dental acrylic fixation. Similar procedure was performed for virus injection in TH::Cre mice targeting LC NA neurons (AP: –5.46 mm, ML: ± 1.2 mm, DV: –3.6 mm). Mice were allowed to recover for at least 2 weeks to get sufficient virus expression before connecting to the EEG/EMG recording cables and optical stimulation patch cord. EEG/EMG electrode and fiber optic implantation were omitted in the mice infected with ChR2-eYFP or eYFP viruses used for in vitro electrophysiology experiments. Fiber photometry

For fiber photometry, 0.3 ml AAV vectors encoding GCaMP6f (AAV-DJ-EF1a-DIO- GCaMP6f, 1.1 × 1012 gc/ml, Stanford Virus Core, Lot no. 3725) were delivered to LH (AP: −1.35 mm, ML: ± 0.95 mm, DV: −5.15 mm) of young (3 to 5 months) or aged (18 to 22 months) Hcrt::Cre mice with a 5 ml Hamilton micro-syringe. A glass fiber (400 mm core diameter, Doric Lenses) was implanted with the tip at the injection site for GCaMP6f signal acquisition afterwards. EEG/EMG electrodes were implanted following fixation of fiber optic and secured with Metabond and dental acrylic. Mice were allowed to recover for at least 2 weeks to get sufficient virus expression before connecting to the EEGEMG recording cables and fiber photometry recording patch cord. Single-nucleus RNA-sequencing (snRNA-seq)

To label telomeres in the nuclei, 0.3 ml AAV vectors encoding Cre-dependent DsRed-hTRF2 (52) (AAV-DJ-DIO-DsRed-hTRF2, 1.95 × 1012 gc/ ml, customer viruses packaged at Stanford Virus Core, Lot no. 4422) were bilaterally injected to 8 of 14

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the LH (AP: −1.35 mm, ML: ± 0.95 mm, DV: −5.15 mm) of young (3 months) and aged (18 months) male and female Hcrt::Cre mice [3 mice per condition (young/aged male/ female)]. EEG/EMG recording and analysis

Mice were singly-housed after surgery and allowed to recover for 1 week with access to food and water ad libitum before EEG/EMG recording. EEG/EMG signals were amplified through a multiple channel amplifier (Grass Instruments) and acquired with VitalRecorder (Kissei Comtec Co.) with a sampling frequency of 256 Hz followed by offline signal analysis. The bandpass was set between 0.1 and 120 Hz. Raw EEG/EMG data were exported to Matlab (MathWorks, Natick, MA, USA) and analyzed with custom scripts and Matlab built- in tools based on described criteria (12) to determine behavioral states. Cataplexy-like EEG/EMG pattern was determined based on the criteria described in the original publication reporting the OX(Hcrt)-ataxin3 narcolepsy mouse model (15) and the consensus definition of cataplexy in mouse models of narcolepsy: (i) ≥ 10 s of EMG atonia; (ii) EEG with theta band domination; (iii) behavioral immobility preceded by ≥ 40 s of wakefulness (30). For optogenetic and fiber photometry recording experiments, simultaneous EEG/EMG signals were recorded to determine behavioral states. The latency of sleep-to-wake transition and the duration of wakefulness following optogenetic stimulation during sleep were determined in SleepSign (Kissei Comtec Co.) with indication of stimulation timestamps on the raw EEG/ EMG signals. EEG power spectral analysis was performed with the same method as described earlier (13). EEG band power calculation was based on: delta (1 to 4 Hz); theta (4 to 12 Hz). EEG band power comparison between vehicle- and KCNQ2/3 ligand-treated groups was conducted based on signals during 1 hour (for vehicle versus XE991) and 3 hours (for vehicle versus flupirtine) following injection for wakefulness and NREM sleep based on the dynamic of drug’s effect. As both XE991 and flupirtine postponed REM sleep onset, EEG band power was computed based on the initial REM sleep epoch after injection of vehicle/drug. The investigator was blind to the group information while conducting the EEG/ EMG data analysis. In vivo optogenetic stimulation

After recovery and sufficient virus expression (>2 weeks), mice injected with viruses expressing Cre- dependent ChR2-eYFP were connected to EEG/EMG recording cables and fiber optic patch cords (200 mm core diameter, Doric Lenses) for one week acclimation in special cages with open top which allowed mice to move freely. Following acclimation, optogeLi et al., Science 375, eabh3021 (2022)

netic stimulation with a range of frequencies (1, 5, 10, 15, and 20 Hz, controlled by A.M.P.I. Master 8) and a range of blue light (473 nm) intensities (1, 5, 10, 15, and 20 mW, Laserglow Technologies, calibrated with Thorlabs light meter) was performed. Each stimulation train consisted of 15 ms light pulses for 10 s with a given light intensity and frequency according to a randomized 5 (light intensities) × 5 (frequencies) matrix generated in Matlab. Sleep-to-wake transition experiments were performed between ZT5-ZT9 of their inactive phase when mice have a strong sleep pressure. Light stimulations were delivered to mice within 30 s of NREM or REM sleep onset to determine the latency of sleep-to-wake transition and duration of wake bout following optogenetic stimulation. The onset of light stimulation was time-stamped during recording for offline analysis afterwards. Fiber photometry signal acquisition and analysis

After recovery, sufficient virus expression (>2 weeks), and habituation to EEG/EMG cable and fiber optic patch cord (400 mm core diameter, Doric Lenses), mice injected with AAV viruses expressing Cre-dependent GCaMP6f were connected to EEG/EMG recording setup and a custom-built fiber photometry setup (50). Briefly, a 470-nm LED (M470D3, Thorlabs, NJ, USA) was sinusoidally modulated at 211 Hz and passed through a GFP excitation filter followed by a dichroic mirror (MD 498, ThorLabs) for reflection. The light stream was sent through a high NA (0.48), large core (400 mm) optical fiber patch cord (Doric Lenses, Québec, Canada), which was connected with a zirconia connector (Doric Lenses, Québec, Canada) to the dental acrylic-secured fiber optic implant (0.48NA, 400 mm, Doric Lenses, Québec, Canada) with the tip on the injection site. Separately, a 405-nm LED was modulated at 531 Hz and filtered by a 405-nm bandpass filter and sent through the optical fiber patch cord to mouse brain to evoke reference fluorescence, which was independent of Ca2+ release. GCaMP6f fluorescence and reference fluorescence were sampled by the same fiber patch cord through a GFP emission filter (MF525-39, ThorLabs), and center-aligned to a photodetector (Model 2151, Newport, Irvine, CA, USA) with a lens (LA1540-A, ThorLabs). The analog signals were amplified by two lock-in amplifiers for GFP fluorescence and reference fluorescence respectively (30 ms time constant, model SR380, Stanford Research Systems, Sunnyvale, CA, USA). Matlab-based custom software was used to control the LEDs and sample both the GFP fluorescence and reference fluorescence through a multifunction data acquisition device (National Instruments, Austin, TX, USA) with 256 Hz sampling frequency in a realtime manner. DF/F was obtained by subtracting the reference fluorescence signal from

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the 470-nm excited GFP emission signal to remove the system interference. The optical fiber patch cord was photobleached to minimize autofluorescence prior to recording according to the user manual (Doric Lenses, Québec, Canada). The recording was conducted between ZT5-ZT9 of their inactive phase when mice have a strong sleep pressure. To reveal the Hcrt neuronal activity in driving behavioral pattern changes, we used a bottom-up analysis strategy, i.e., GCaMP6f data were staged independent of simultaneous EEG/EMG signals. We then separated the increased GCaMP6f into two categories: GCaMP6f transients during sleep (GS) and GCaMP6f epochs associated with wakefulness (GW) (Fig. 1). All the GS and GW were staged from the same amount of recording conducted during ZT5-ZT9 from equal group size (1 hour/ each mouse, n = 6 mice each group) for comparison of Hcrt neuronal activity between young and aged mice. All the GCaMP DF/F transients with a Z score >1% (equals GCaMP6f DF/F value ~0.3-0.6 for individual animal) of the highest DF/F value of the entire trace were staged. After data staging, each GCaMP6f epoch was normalized to its own 5 s baseline with time 0 defined for the beginning of GCaMP6f rising phase. Heatmaps were generated for each category based on 10 s of normalized GCaMP6f epochs with 5 s prior to and 5 s after time 0. A Z score was calculated by subtracting the mean value of GCaMP6f trace prior to time 0 from the mean value of GCaMP6f after time 0 and an averaged Z score based on each animal was used for statistical comparisons. As the GS Z score was generally small, only the GS transients with Z score > mean (GS Z score) – 3 × SEM (GS Z score) were included with ideal signal-to-noise ratio for subsequent analyses. By definition, all the GW epochs were qualified for analyses. GS scatter plot was generated with the duration of GS against its peak value, and GW scatter plot was generated with the duration of wake-associated GW epoch against its maximum peak value (maximum GCaMP6f DF/F, if given epoch appeared with multipeaks). Animal-based frequencies of GS and GW were compared between the young and aged groups. Durations of sleep, wake, and S-W epochs were compared. Spearman correlation analysis with a linear fit was perform between GW frequency (counts/hour) and mean sleep bout duration. The investigator was blind to the group information while conducting the GCaMP6f data staging. Chemical preparation and application

XE991 dihydrochloride (Cat. no. 2000, referred to as XE991) and flupirtine maleate (Cat. no. 2867, referred to as flupirtine) were purchased from Tocris. XE991 was prepared in saline with a concentration of 50 mM for in vitro electrophysiology and prepared in saline 9 of 14

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with a concentration of 0.2 mg/ml for in vivo experiment with a dosage of 2 mg/kg (0.1 ml/ 10 g, intraperitoneally). 5 mM flupirtine stock solution (0.9% saline containing 0.3% dimethyl sulfoxide/DMSO, v/v) was added to artificial cerebrospinal fluid (ACSF) to reach a concentration of 50 mM for in vitro electrophysiology. Flupirtine was prepared at a concentration of 2 mg/ml in 0.9% saline containing 0.3% DMSO (v/v, vehicle) for in vivo experiments with a dosage of 20 mg/kg (0.1 ml/10 g, intraperitoneally). Flupirtine solution was ultrasonicated prior to application. Counterbalanced crossover design was used for in vivo pharmacology experiments to reveal the drug’s effect. Two rounds of drug administrations were separated by at least one week for a complete wash-out of drug’s effect. 4-Aminopyridine (4-AP) was purchased from Sigma-Aldrich (Cat. no. 275875). 100 mM 4-AP stock solution (0.9% sodium chloride/saline as vehicle) was added to ACSF to reach a concentration of 50 mM for in vitro electrophysiology of IM experiment. MK6096 (Merck) was prepared at a concentration of 2 mg/ml in a mixture (v/v, vehicle) of 50% 0.9% saline and 50% Poly ethylene glycol (average Mn 400, PEG400, Sigma-Aldrich Cat. no. 202398) for in vivo pharmacology experiment as previously described (13). In vitro electrophysiology

All the in vitro electrophysiology experiments were performed during the light phase (ZT3ZT9). 3-9 mice were used each group. Slices were randomly assigned to groups examining effects of XE991 or flupirtine on M current in the in vitro pharmacology experiments. Slice preparation

Mice from both groups were decapitated after anesthesia with sevoflurane or perfused with ice-cold slicing solution under anesthesia. To increase the chances of acquiring a healthy slice, we used a sucrose-based or choline-based ACSF for brain slice preparation to reduce the cell excitotoxicity and loss during slice preparation (53). After decapitation, the brain was rapidly dissected and immersed in ice-cold sucrose/choline-based ACSF slicing solution (pH 7.4, 95% O2 / 5% CO2). 300 mm-thick coronal brain slices containing Hcrt neurons with eYFP fluorescence were sectioned using a VT1200s vibratome (Leica Microsystems). After ~20 min incubation at ~35°C, the slices were stored at room temperature. Slices were used for maximally 5 hours after dissection. Experiments were performed at room temperature 21° to 24°C. Recording and data analysis

During experiments, slices were superfused with a physiological extracellular solution containing: 125 mM NaCl, 2.5 mM KCl, 25 mM NaHCO3, 1.25 mM NaH2PO4, 25 mM D-glucose, Li et al., Science 375, eabh3021 (2022)

2 mM CaCl2, and 1 mM MgCl2 (pH 7.4 in 95% O2/5% CO2, ~325 mOsm). Neurons were chosen based on eYFP expression and visualized with an Olympus BX51WI with Nomarski optics connected to a camera (Q-imaging). Thick wall borosilicate pipettes (1B150F-4, World Precision Instruments Inc.) were pulled using a P-97 puller (Sutter Instruments) and electrodes with a resistance of 3-6 megohms were used for recording. Intracellular solution used for whole-cell recording contained: 120 mM K-methyl-sulfonate, 10 mM NaCl, 10 mM EGTA, 1 mM CaCl2, 10 mM HEPES, 0.5 mM NaGTP, 5 mM MgATP, pH adjusted to 7.2 with KOH, osmolarity adjusted to 305 mOsm with sucrose; 0.2% biocytin was added for post-hoc staining. Neurons were recorded under current-clamp to examine excitability, or under voltage-clamp to examine PSCs. 1 s step currents from –50 pA to 300 pA were used to evoke AP firing. For optogenetic stimuli, a 15-ms blue light pulse (3.4 mW, calibrated with Thorlab light meter) was given at 1 Hz, 5 Hz, 10 Hz, 15 Hz, and 20 Hz in a randomized manner for 10 s to compare light-induced activity between the young and aged groups, and the interval between sweeps was 20 s. Data were acquired with a Multiclamp 700B amplifier (Axon Instruments, USA), and sampled at 10 kHz. Stimulus generation and data acquisition were performed using pClamp 10. Data were analyzed using Stimfit 0.14.9 (www.stimfit.org) and R 3.5.1 (the R project for statistical computing). RMP values were measured and averaged from temporal windows (at least 50 ms prior to the peak of a given AP for spontaneously firing neurons) with minimal membrane potential variance (54). The RMPs were determined without predicted/measured junction potential correction. All the amplitudes of APs and spikelets were calculated from RMPs. Depolarization events with a peak value above –20 mV, and with a half width shorter than 6 ms were qualified for spikelet analyses. PSC recording from non-fluorescent neuron innervated by fluorescent Hcrt neuron expressing ChR2-eYFP was performed as illustrated in fig. S4A. For the PSC failure analysis, a success PSC was considered when a current deflection bigger than 10 pA occurred time-locked to the light pulse. The investigators were blind to the group information while conducting the data analyses. LC neurons were recorded in slices prepared from WT young (2 to 3 months) and aged (18 to 21 months) mice, infused with biocytin, followed by antibody staining against tyrosine hydroxylase (TH). Only the neurons positive for both biocytin and TH were included for data analyses. IM recording

For recording of the slowly deactivating M-current (IM) mediated by KCNQ2/3, perfo-

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rated patch recordings were used to maintain the integrity of second messenger signaling cascades and minimize current rundown. The pore-forming antibiotic nystatin was dissolved in DMSO at 50 mg/ml. This stock solution was diluted in an internal pipette solution and vortexed and ultrasonicated for a final concentration of 100 to 200 mg/ml. Pipette tips were prefilled by brief immersion into antibioticfree solution and then pipettes were back filled with nystatin. After the cell-attached configuration was attained, the access resistance was periodically monitored with hyperpolarizing voltage steps (10 mV, 20 ms) and capacitative transients were cancelled. After 10 to 20 min, recording was started once the access resistance stabilized. The recording was terminated if a sudden change in access resistance occurred. Extracellular solution contained 4-AP (5 mM) to minimize contamination by other potassium currents, and AMPARs, glycine receptors and GABAA receptors were blocked by 6,7dinitroquinoxaline-2,3-dione (DNQX, Tocris Cat. no. 0189, 10 mM), strychnine (SigmaAldrich Cat. no. S0532, 1 mM), (2R)-amino-5phosphonopentanoate (APV, Tocris Cat. no. 0106, 100 mM) and bicuculline (Sigma-Aldrich Cat. no. 285269, 10 mM). IM was recorded using a standard deactivation protocol (1000 ms hyperpolarizing steps to -30 mV from a holding potential of –20 mV every 10 s, intersweep holding potential –20 mV). IM did not inactivate with this protocol, while contamination by other voltage-gated currents was minimized. IM was measured as the inward relaxation current caused by deactivation of IM during this voltage step (Fig. 4, G and H). After obtaining at least a stable 5 min baseline, XE991 (50 mM) or flupirtine (50 mM) was applied. The effect of XE991 or flupirtine was determined by comparing averaged IM amplitudes over a 5 min period just before XE991 or flupirtine application with averaged IM amplitudes during the 5 to 10 min period after XE991 or flupirtine application. Array tomography (AT) Tissue preparation

Array creation and immunohistochemistry were described in detail in a previous publication (55). In short, a small piece of tissue (~2 mm high by 1 mm wide by 1 mm deep), covering the LH containing eYFP-labeled Hcrt neurons, was microwave-fixed in 4% Paraformaldehyde (PFA). The fixed tissue was then dehydrated in graded steps of ethanol, and then embedded in LR White resin overnight at 50°C. The embedded tissue was sectioned on an ultramicrotome at a thickness of 70 nm and placed as a ribbon array directly on gelatin or carbon coated glass coverslips. The ultrathin physical sectioning allows AT to achieve true isotropic voxels of ~100 nm. To assure that the brain tissue from animals were 10 of 14

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prepared and imaged in as similar conditions as possible, all samples were paired starting at the tissue preparation step. Thus, young and aged animals were prepared in tandem, placed on the same coverslip, stained together and imaged together. Furthermore, to minimize the impact of locational differences in the gathered tissue, multiple blocks were generated from LH of each mouse, and screened at 20× using 4′,6diamidino-2-phenylindole (DAPI) fluorescence. Then similar tissue blocks were used for further analysis. Immunohistochemistry

Immunohistochemistry was then carried out on the arrays using primary antibody against KCNQ2 (Alomone Cat. no. AGP-065). The primary antibodies were visualized via fluorescencelabeled secondary antibody (Alexa 594, Invitrogen Cat. no. A11076), and mounted in SlowFade Gold antifade with DAPI (Invitrogen Cat. no. S36938). Microscopy

Wide-field imaging of ribbons were accomplished on a Zeiss Axio Imager.Z1 Upright Fluorescence Microscope with motorized stage and Axiocam HR Digital Camera as previously described (56). A position list was generated for each ribbon array of ultrathin sections using custom software modules written for Axiovision. Single fields of view were imaged for each position in the position list using a Zeiss 63×/1.4 NA Plan-Apochromat objective. Image registration and processing

Image stacks from AT were imported into Fiji (ImageJ) and aligned using both rigid and affine transformations with the Register Virtual Stacks plugin. The aligned image stacks were further registered across image sessions using Fiji and TrackEM. The aligned and registered image stacks were imported into Matlab and deconvolved using the native implementation of Richardson-Lucy deconvolution with empirical or theoretical PSFs with 10 iterations (56). Custom functions were written to automate and facilitate this workflow. eYFP segmentation

eYFP delimited protein amount was calculated using custom Matlab software. eYFP volumes were slightly dilated via morphological operations and used to segment protein data in image space. Segmentation custom functions were used to quantify the number and amount of proteins encapsulated by eYFP. Single-nucleus isolation, FACS sorting, RNA library preparation and sequencing

3 weeks after virus injection, mice were deeply anesthetized using isoflurane and perfused with 1× PBS. The brains were rapidly dissected and transferred to a chilled metal Brain Slicer Li et al., Science 375, eabh3021 (2022)

Matrix (Zivic Instruments, 500 mm coronal slice intervals), and the brain sections containing Hcrt neurons (AP: –1.0 ~ –2.0 mm) were sliced and transferred to 1× PBS on ice. Bilateral hypothalamic areas (LH) were identified and dissected under a stereoscope. LH tissue blocks were then transferred to a glass dounce homogenizer (Sigma-Aldrich) on ice and homogenized in 1 ml Homogenization Buffer (57) containing Tris (pH 8.0, 10 mM), sucrose (250 mM), KCl (25 mM), MgCl2 (5 mM), Triton-X100 (0.1%), RNasin Plus RNase Inhibitor (0.5%, Promega Cat. no. N2615), SUPERase·In RNase Inhibitor (0.5%, ThermoFisher Cat. no. AM2694), Protease Inhibitor Cocktail (1×, Promega Cat. no. G6521), DTT (0.1 mM) and DAPI (1:1000, Invitrogen Cat. no. D3571). LH tissue blocks from 3 mice per condition (young/aged male/female) were pooled each condition for isolation of nuclei. The nuclei were released by sequentially applying 10 to 12 strokes of the loose dounce pestle and 10 to 12 strokes of the tight dounce pestle on ice, followed by filtering the suspension through a 35 mm cell strainer (Falcon). The nuclei were then spun down by centrifugation (10 min, 900× g at 4°C) and resuspended in the Wash Buffer (1× PBS containing 0.8% BSA, 0.5% RNasin Plus RNase Inhibitor and 0.5% SUPERase·In RNase Inhibitor). The single-nucleus suspension was further washed twice in Wash Buffer by centrifugation (10 min, 900× g at 4°C). Fluorescence activated cell sorting (FACS) was performed using the 70-mm nozzle and optimal gates collecting the DsRed/ DAPI double positive events and excluding debris and doublets. Sorted DsRed+ single nuclei were confirmed using a fluorescence microscope, and manually counted using a hemocytometer. snRNA-seq libraries were prepared using 10x Genomics Chromium Single Cell 3′ Reagents v3 following manufacturer’s instructions. Briefly, the concentration of single nuclei solution prepared from dissected LH tissue was determined using DAPI staining and Trypan Blue staining. The nuclei solution was loaded onto a Chromium Chip B to capture seven to ten thousand nuclei in droplets containing the reverse transcription reagents. After reverse transcription, the now barcoded cDNA was recovered and amplified for 12 polymerase chain reaction (PCR) cycles. After qualitative and quantitative control of the cDNA, the final libraries were constructed by fragmenting the cDNA, End Repair, and A-Tailing. After adapter ligation, the libraries were amplified for 11 PCR cycles. The libraries were sequenced using an Illumina MiSeq v3 150-cycle kit to check library quality and confirm the number of captured nuclei. Then all the barcoded samples were mixed and deep sequenced on an Illumina HiSeqX sequencing machine across 4 different lanes to avoid lane variability and potential lane failure.

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snRNA-seq data analysis

Illumina fastq files were processed through the 10x Genomics cellranger pipeline according to the manufacturer’s instructions. Briefly, reads were aligned to the mm10 mouse genome using a custom gtf annotation file which labeled all “transcripts” as “exons,” thus allowing to count intronic as well as exonic reads. The four libraries were then combined using cellranger aggr command to match sequencing depth per cell across libraries. All further processing of the genes X cells count matrix was performed in Seurat V3 (58) using scTransform normalization (59). First, the population of Hcrt+ neurons were identified out of all sequenced cells by coarse Louvian clustering of the entire sequencing dataset. Only one cluster showed Hcrt expression. This cluster was then separately subclustered, and all doublet clusters were removed. No large batch effects were observed at this level. A core set of three clusters, all of which expressed Hcrt at high levels, served as the basis for the analysis of age related effects. CRISPR/SaCas9-mediated Kcnq2/3 gene disruption in Hcrt neurons

The target sites of Kcnq2/3 genes for Staphylococcus aureus CRISPR/Cas9 (CRISPR/SaCas9) were designed by CHOPCHOP (http://chopchop. cbu.uib.no) (60). The target sequences were as follows: sgKcnq2: 5′-CGCGTGTGGAGTCGGGCGCGC3′, sgKcnq3: 5′-GCGGCCACCGCCCTCCAGCAG-3′. Oligonucleotides encoding guide sequences were purchased from Sigma-Aldrich and cloned individually into BsaI fragment of pX601 (Addgene plasmid 61591). U6-sgKcnq2 and U6-sgKcnq3 fragments were PCR-amplified, respectively using pX601-sgKcnq as a template. Amplified fragments were cloned tandemly into MluI-digested pAAV CAG FLEX mCherry by Gibson assembly method. The primers used were as follows; Gibson1-F: 5′-TAGGGGTTCCTGCGGCCGCAGAGGGCCTATTTCCCATG-3′, Gibson1-R: 5′-ATAGGCCCTCTCTAGAAAAAATCTCGCCAAC-3′, Gibson2-F: 5′- TTTTTCTAGAGAGGGCCTATTTCCCATG-3′, Gibson2-R: 5′-TCATTATTGACGTCAATGGAAAAAATCTCGCCAACAAGTTG-3′. AAV constructs carrying nontargeting guide sequences (5′-GCGAGGTATTCGGCTCCGCGT-3′) were used as control. For the Cre- dependent SaCas9 construct, SaCas9 fused with 3× HA tag was PCR amplified using pX601 as a template. Amplified fragment was cloned into AscI/NheI-double digested pAAV-U6-SaCas9gRNA(SapI)-CMVSaCas9-DIO-pA (Addgene plasmid 113691). Next, the plasmid was digested by MluI and applied to self- ligation to remove U6 promoter and single-guide RNA (sgRNA) scaffold sequences. pAAV CMV-DIO-SaCas9-3HA (SaCas9), pAAV U6 sgKcnq2-U6 sgKcnq3 CAG FLEX mCherry (sgKcnq2/3) and pAAV U6 sgControl-U6 sgControl 11 of 14

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CAG FLEX mCherry (sgControl) were packaged into AAV-DJ by the Wu Tsai Neurosciences Institute Gene Vector and Virus Core at Stanford University. 20 young (6 to 8 weeks old) Hcrt::Cre mice were separated into two groups in a random manner (n = 10/group). Under anesthetics and analgesic, according to the Hcrt neuron field coordinates as described above, one group received bilateral stereotaxic injection of a 0.6 ml (each side, 0.3 mm apart in depth) mixture of SaCas9 (2.4 × 1013 gc/ml) and sgControl (6.24 × 1012 gc/ml) and implanted with EEG/EMG electrodes to serve as the control group. The other group received bilateral stereotaxic injection of a 0.6 ml mixture of SaCas9 and sgKcnq2/3 (2.97 × 1012 gc/ml) and implanted with EEG/ EMG electrodes to monitor the effect of Hcrt neuron- selective Kcnq2/3 gene disruption on sleep architecture. After surgery, mice were connected to EEG/EMG recording cables and singly-housed with food and water ad libitum to recover, and for EEG/EMG signal recording. EEG/EMG signals were recorded continuously on day 6 and day 7 weekly up to 8 weeks (EEG/ EMG recording lasted until 12 weeks in half of each group) after surgery. Following recording in week 8/12 after virus injection, slices were prepared from each group for in vitro electrophysiology experiment to determine RMP and firing property of the Hcrt neurons labeled by mCherry flag. Patch clamp recorded cells were infused with biocytin for subsequent immunostaining. The data were used for statistical analysis only if the recorded neurons were stained to co-express biocytin and HA tag. Histology

For in vivo experiments, upon accomplishment of recordings, mice were perfused under anesthesia described above with ice-cold 1× PBS and followed by 4% PFA for immunostaining against Hcrt1/OXA for Hcrt neurons, and TH for LC NA neurons. Brains were rapidly extracted, postfixed with 4% PFA at 4°C overnight, and equilibrated in 30% sucrose in 1× PBS containing 0.1% NaN3. Then, brains were sectioned at –22°C with a cryostat (Leica Microsystems) at a thickness of 35 mm. Slices were collected from anterior to posterior consecutively to 24-well plates containing PBS with 0.1% NaN3, covered with aluminum foil, and stored at 4°C until immunostaining and imaging. Primary antibody against OXA/Hcrt1 (SC-8070, Lot no. A2915, Goat polyclonal IgG) was purchased from Santa Cruz Biotechnology. Primary antibody against TH (Chicken polyclonal anti-peptide, Cat. TYH, Lot no. TYH1897983) was purchased from Avēs. Primary antibody against HA tag (Rabbit Anti-HA tag pAb, Item no. 561, Lot no. 067) was purchased from MBL International Corporation. Secondary antibodies: Alexa Fluor 488 Goat anti-chicken IgG (H+L, Ref. no. A11039, Lot no. 1094413), Alexa Fluor Li et al., Science 375, eabh3021 (2022)

488 donkey anti-goat IgG (H+L, Ref. no. A11055, Lot no. 1869589), Alexa Fluor 488 donkey anti-rabbit IgG (H+L, Ref. no. A21206, Lot no. 1910751), Alexa Fluor 647 donkey anti-goat IgG (H+L, Ref. no. A21447, Lot no. 2175459), were purchased from Invitrogen (Manufacturer: Life Technologies). Alexa Fluor 594 streptavidin conjugate (Ref. no. S11227, Lot no. 1991448) and Alexa Fluor 647 streptavidin conjugate (Ref. no. S32357, Lot no. 1738557) to label neurons infused with biocytin were purchased from Invitrogen. For the WT mice used for comparison of sleep patterns, sections around LH and LC were washed in 1× PBS for 5 min, 3 times and incubated in a blocking solution of PBS with 0.3% Triton X-100 (PBST) and 4% bovine serum albumin (BSA) for 1 hour. Following that, OXA/Hcrt1 primary antibody was added to the blocking solution (1:800) overnight. On the second day, sections were washed in 1× PBS for 3 times (5 min/time), and incubated in blocking buffer for 2 hours. After blocking, secondary antibody was added to the blocking buffer for 2 hours (dilution 1:800). After 3 times of 5-min 1× PBS washing, brain sections were mounted onto gelatin-coated slides, covered with Fluoroshield containing DAPI mounting media (Sigma-Aldrich, F6057) and cover glass for imaging with wild field microscope (Zeiss AxioImager, Germany) for entire section or LSM710 Confocal Microscope for enlarged visualization (Zeiss, Germany). For brain slices infected with Cre-dependent viruses, slices around the injection site were collected and stained with appropriate antibodies as described above. Alexa Fluor 594 streptavidin conjugate or Alexa Fluor 647 streptavidin conjugate for staining of biocytin was added together with the secondary fluorescent antibody for Hcrt1, TH or HA tag on the second staining day for in vitro experiment slices. Object recognition test

Aged mice (~20 months, singly-housed with a reversed 12 hours/12 hours light/dark cycle, 9 pm light on, Zeitgeber time 0/ZT 0) were used to evaluate flupirtine’s effect on memory ability in the object recognition task. The object recognition task was performed according to a protocol described by Leger et al. (61). The protocol consisted of habituation, familiarization and test sessions (fig. S8). During each habituation session, an individual mouse was released to the arena (34 cm × 17 cm, nontransparent open field filled with Sani-Chip pine bedding floor) for habituation of 5 min. Each mouse underwent two habituation sessions conducted during ZT16-18 and ZT22-24 for 3 consecutive days. During the familiarization session (Day 4: ZT22-24), each mouse was allowed to explore two identical objects for a total of 5 min. Each object was placed at the same distance from the walls and corners of the field without spatial or odor cues (bedding

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was changed; arena and objects were cleaned with 70% ethanol before each exposure). After the familiarization session, mice were intraperitoneally injected with either vehicle or flupirtine (20 mg/kg) at the beginning of the following light phase. During the test session (Day 5: ZT22-24), mice were placed in the same arena with one of the familiar objects from the familiarization session replaced by a similar size novel object. The position of the novel object (left or right) was randomized for each mouse and each group tested. Time spent facing away from object within the 7 cm radius or climbing on object was not qualified as exploration. Mice were randomly assigned to control/ flupirtine group through a counterbalanced crossover design. Two rounds of object recognition task (with two sets of familiar and novel objects) were separated by one week for a complete drug wash-out. Animal-based averaged value of two rounds of familiarization was presented. Mouse with over 65% preference for either object during the familiarization session was not qualified to proceed to the next session. Statistics

One/two hour-binned sleep comparisons were analyzed by two-way repeated measure (RM) analysis of variance (ANOVA) (linear mixedeffects model for counterbalanced crossover design) followed by Šidák’s multiple comparisons. Holm-Šidák was used for comparison based on 24 hours/light/dark phase. Unpaired t-test with Welch’s correction was used for GCaMP6f data and in vivo optogenetic data analyses. For slice electrophysiology, MannWhitney U test, RM one-way ANOVA, two-way ANOVA were used to analyze appropriate datasets. Paired test was used for data analyses of experiments with paired design. Spearman correlation with a linear fit was performed for 2-demensional data correlation analysis. For snRNA-seq data, differentially expressed genes across ages were determined using the Wilcoxon rank-sum test, considering only those genes with a Bonferroni adjusted P < 0.05. Differences with P < 0.05 were considered significant for all experiments. In figures, *, **, ***, ****, and † indicate P < 0.05, P 10-fold when the ER signal peptide was exposed (60 amino acids). Thus, the emergence of a hydrophobic signal peptide, but not another type of nascent chain, weakens the interaction of the NAC globular domain with the ribosome. We then investigated the role of the two ribosome-binding antiparallel helices that dock the globular domain on the ribosome in proximity to the emerging nascent chain. The helices are amphipathic and orient the positively charged side toward the ribosome surface, whereas the hydrophobic side contributes to a buried hydrophobic pocket (fig. S5). These helices were sensitive to proteolysis when human NAC was subjected to crystallization (15), suggesting that they are flexibly disposed in solution but are apparently stabilized in the ribosome-bound state. To test this, we engineered two cysteines in the helices such that they would be apposed to each other in the ribosome-bound NAC structure. Consistent with our hypothesis, the engineered cysteines formed a disulfide bond after oxidant treatment only in the presence of the ribosome (Fig. 2A and fig. S9). To investigate whether the emergence of the signaling peptides may destabilize and

release the globular domain of NAC from the ribosome (Fig. 2B), we incorporated photocross-linking probes both inside and outside the hydrophobic pocket (Fig. 2B) and tested their proximity to nascent chains coding for a cytosolic, mitochondrial, or ER protein. NAC variants carrying the probe within the hydrophobic pocket (e.g., NACa-I121) cross-linked to ER targeting signals (Fig. 2C and fig. S10, A to C). Cross-linking was dependent on nascent chain length and was only seen once the targeting signal was fully exposed outside the exit tunnel (fig. S10A). Cross-linking was prevented when the helices were covalently linked by disulfide bond formation, demonstrating that destabilization of the NAC globular domain by the ER signal peptide requires separation of the helices (Fig. 2D). Furthermore, cross-linking to the pocket residues NACa-I121 and NACb-L48, but not the less buried NACa-M80, was modulated by changing targeting signal hydrophobicity (fig. S10D). Mutating M80 to serine impaired nascent chain photo-cross-linking to NACaI121 (Fig. 2E), which suggests that this residue also contributes to nascent chain sensing. These results indicate that an ER signal sequence destabilizes the NAC globular domain. The NACb N-terminal tail remains anchored to the ribosomal surface regardless of the nascent 25 FEBRUARY 2022 ¥ VOL 375 ISSUE 6583

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Fig. 3. Structure of the ribosome•SRP•NAC complex. (A) Cryo-EM structure of the RNCss•NAC•SRP complex. Boxed region indicates the closeup shown in (B). (B) Ribosome tunnel exit regions depicting the SRP54 NG and M domains, the NACa UBA domain, and the NACb anchor domain are colored slate, cyan, orange, and green, respectively. Underlying EM density is shown as a transparent surface. (C) Closeup on the UBA interactions with SRP54 NG domain shown as cartoon and sticks, fitted into cryo-EM densities shown as mesh. (D) Schematic representation of the ternary complex. Boxed region shows

chain, as evidenced by cross-linking between a residue in the NACb anchor and the ribosomal protein eL22, whereas a probe in the N terminus of NACa changed its location only for the ER substrate (fig. S11). Combined, these results suggest that NAC interactions with the ribosome are remodeled as the signal peptide emerges from the ribosome tunnel. Flexibly tethered UBA domain of NAC recruits SRP

The cryo-EM data on RNCSS mixed with both NAC and SRP also allowed us to visualize the complex with NAC and SRP simultaneously 842

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sequence alignment of NACa UBA domain in eukaryotes. (E) Summary of the Kd values for the binding of wild-type and mutant SRPs to RNCSS•NAC, based on fitting of the data in fig. S17A. N.D., not determined. (F) and (G) Fluorescence microscope images of hsp-4p::GFP worms (F) and worm flow cytometry analysis of ssGFP (G) in worms carrying the indicated RNA interference (RNAi)Ðresistant genes in the endogenous RNAi background. Box plot center line indicates the median, box length the upper and lower quartile, and whiskers the minimum/ maximum quartile (N ≥ 2000).

bound to the ribosome (RNCss•NAC•SRP) (Fig. 3A and figs. S1 and S12). The conformation of SRP in the ternary complex was similar to that of previously observed SRPribosome complexes (3, 4). The density for the NACb anchor was observed in a similar position as in the RNC•NAC complexes (fig. S12C). However, the globular domain of NAC was no longer resolved, because its binding position at the tunnel exit was occupied by the SRP54 M domain (Figs. 1G and 3, A to D). In addition, we observed density for the flexibly tethered C-terminal UBA domain of NACa

bound to the N domain of SRP54 (Fig. 3, B and C, and figs. S12 and S13). The interactions occupied two patches of contact points and involved a number of salt bridges and specific hydrogen bonds between highly conserved residues (Fig. 3, C and D, and fig. S14). The UBA-binding site on SRP54 overlapped with the binding site of the NG domain of SR (fig. S15), which suggests that formation of the SRP•SR complex will displace NAC from SRP at the ER membrane (22–24). The direct interaction of the UBA domain of NAC with SRP raises questions as to whether it plays a role in ER targeting. science.org SCIENCE

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To address this, we generated the following: (i) a NAC mutant in which the UBA is deleted (dUBA), (ii) a NAC mutant (D205R/N208R-NACa, named UBAmt), and (iii) an SRP mutant (K50E/ R53E-SRP54, named SRP54mt on the basis of human sequence numbering). UBAmt and SRP54mt contain charge reversal mutations at contact points between the UBA and the NG domain of SRP54. We measured the effects of these mutations on the binding affinity of SRP for NAC-engaged RNCSS displaying the ER signal sequence. Although none of the above-described mutations changed the affinity of NAC or SRP for SR or RNCs (figs. S16 and S17), they all decreased the affinity of SRP for the RNCSS•NAC complex by >5-fold (Fig. 3E and fig. S17A). The same effect was observed in reciprocal experiments when NAC was titrated to a preformed RNCSS•SRP complex (fig. S17, B and C). Thus, the contact between NAC UBA and SRP54 NG domains stabilizes the cobinding of SRP and NAC on signal sequence–displaying ribosomes. To test whether the UBA domain mediates the initial recruitment of SRP to the ribosome, we used total internal reflection fluorescence microscopy to study single-molecule events in which SRP binds to surface-immobilized RNCSS prebound with NAC (Fig. 4A). If SRP is captured by NAC through the UBA domain before stable engagement with the ribosome, then the arrival of SRP on NAC-bound RNCSS would be synchronous with the onset of FRET between a dye pair engineered on the SRP54 NG and NACa UBA domains. The results were consistent with this model: The initiation of colocalized fluorescence signals from NAC and SRP was synchronous with the onset of FRET in every single-molecule fluorescence time trace (Fig. 4, B and C), even in recruitment events that did not lead to a long-lived SRP association with the RNC (for an example, see Fig. 4B). Statistical analysis, in which the FRET time traces were aligned to the start of the SRP fluorescence signal (n = 45), showed that peak FRET efficiency was coincident with SRP arrival (Fig. 4D). Once a stable RNC•NAC•SRP ternary complex was formed, NACa UBA dynamically associated with and dissociated from SRP54, as shown by the frequent transitions between low- and high-FRET states (Fig. 4E). Thus, the contact between UBA and NG initiates before the productive docking of SRP at the exit of the ribosomal tunnel and signal sequence handover. C. elegans mutants with impaired NAC UBASRP54 NG interactions showed elevated levels of the ER stress reporter hsp-4p::GFP, particularly in highly secretory intestinal cells (Fig. 3F and fig. S18, A and B). Furthermore, the levels of a secreted GFP reporter containing a signal sequence (ssGFP) (25) were significantly lower in NAC UBA and SRP54 NG mutant worms (Fig. 3G and fig. S18, C and D). The mutant worms also showed a cytosolic stress response, suggesting a possible accumulation SCIENCE science.org

of misfolded ER proteins in the cytosol caused by failed targeting (fig. S18E). As mentioned above, the defects observed with SRP54mt were not caused by the impaired interaction with the SR NG domain (figs. S15 and S16). Thus, the contacts between SRP and the UBA domain of NAC are critical for the successful SRP targeting of proteins to the ER. Mechanism of the NAC-SRP interplay on the ribosome to initiate ER targeting

We propose a molecular mechanism for the interplay of NAC and SRP at the ribosome that

controls and initiates cotranslational protein targeting to ER: NAC acts as “gatekeeper” to shield emerging nascent chains from nonphysiological interactions with SRP (Fig. 5). Because of its abundance and high affinity for the ribosome, NAC is bound to most ribosomes at early stages of translation through a high-affinity anchor and a weakly bound globular domain that blocks SRP access to nascent polypeptides. The flexibly tethered UBA domain recruits SRP and increases its local concentration at the tunnel exit region to initiate sampling of nascent chains. The emergence of an

Fig. 4. Interaction between SRP54 and NACa UBA domain mediates initial SRP recruitment to the ribosome. (A) Scheme of the single-molecule experiment. RNC is immobilized on the glass coverslip surface through 3′ biotinylated mRNA (not shown). NAC was labeled with Cy3b (green star) in the UBA domain, and SRP is labeled with Atto647N (red star) in the SRP54 NG domain. (B) and (C) Representative singlemolecule fluorescence time traces. Dem – Dex, donor emission during donor excitation; Aem – Dex, acceptor emission during donor excitation; Aem – Aex, acceptor emission during acceptor excitation; and E, apparent FRET efficiency calculated from the Aem – Dex and Dem – Dex traces. The region after donor photobleaching is masked. (D) Time traces of FRET efficiency (n = 45) aligned to the start of the SRP (acceptor) signal. The median FRET value of all traces at each time frame is plotted as a solid blue line. The blue shaded area encloses the FRET range that includes the first to third quartile of data at each frame. (E) Representative time trace after a stable NAC•SRP•RNC ternary complex is formed. 25 FEBRUARY 2022 • VOL 375 ISSUE 6583

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11. Y. Zhang et al., Mol. Biol. Cell 23, 3027–3040 (2012). 12. H.-H. Hsieh, J. H. Lee, S. Chandrasekar, S. O. Shan, Nat. Commun. 11, 5840 (2020). 13. Y. Liu, Y. Hu, X. Li, L. Niu, M. Teng, Biochemistry 49, 2890–2896 (2010). 14. L. Wang et al., Protein Cell 1, 406–416 (2010). 15. T. Spreter, M. Pech, B. Beatrix, J. Biol. Chem. 280, 15849–15854 (2005). 16. M. Gamerdinger et al., Mol. Cell 75, 996–1006.e8 (2019). 17. R. D. Wegrzyn et al., J. Biol. Chem. 281, 2847–2857 (2006). 18. Z. Lin et al., Science 367, 100–104 (2020). 19. M. Pech, T. Spreter, R. Beckmann, B. Beatrix, J. Biol. Chem. 285, 19679–19687 (2010). 20. J. Jumper et al., Nature 596, 583–589 (2021). 21. M. Calfon et al., Nature 415, 92–96 (2002). 22. K. Wild et al., J. Mol. Biol. 428, 2880–2897 (2016). 23. J. H. Lee et al., Sci. Adv. 7, eabg0942 (2021). 24. K. Kobayashi et al., Science 360, 323–327 (2018). 25. H. Fares, I. Greenwald, Nat. Genet. 28, 64–68 (2001). 26. Y. C. Chen et al., EMBO J. 33, 1548–1564 (2014). 27. R. S. Hegde, E. Zavodszky, Cold Spring Harb. Perspect. Biol. 11, a033902 (2019). 28. T. Hessa et al., Nature 475, 394–397 (2011). 29. V. Okreglak, P. Walter, Proc. Natl. Acad. Sci. U.S.A. 111, 8019–8024 (2014). AC KNOWLED GME NTS

Fig. 5. Model for cotranslational signal sequence handover from NAC to SRP during ER-protein targeting.

ER signal sequence weakens the interactions of NAC’s globular domain with the ribosome. This allows SRP to bind the signal sequence at the exit of the ribosomal tunnel, displacing the globular domain of NAC. NAC remains associated with both the ribosome and SRP through the respective NACb anchor and UBA contacts until it reaches the ER membrane, where SR displaces the UBA domain from SRP. This study resolves the molecular function of NAC as a sorting factor for nascent chains and the nature of its spatiotemporal coordination with SRP on the ribosome. Our results explain how NAC, which binds to virtually all ribosomes, prevents sub-stoichiometric SRP from forming tight but unproductive complexes with signal-less ribosomes while at the same time keeping SRP tethered to allow it to scan for the presence of the ER signal sequence. Because degenerate and highly diverse targeting sequences cannot be recognized with sufficient specificity in a single step and/or by individual targeting factors, stepwise recogni844

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tion by NAC followed by SRP, coupled with quality control pathways (26–29), increases the overall fidelity of protein targeting. The exit region of the ribosomal tunnel is a crowded environment where multiple binding factors compete for the nascent chain. Therefore, it is possible that NAC’s role as a sorting factor extends beyond the recruitment of SRP to orchestrate a multitude of nascent chain–processing events.

RE FERENCES AND NOTES

1. R. Gilmore, G. Blobel, P. Walter, J. Cell Biol. 95, 463–469 (1982). 2. M. Halic et al., Nature 444, 507–511 (2006). 3. R. M. Voorhees, R. S. Hegde, eLife 4, e07975 (2015). 4. A. Jomaa et al., Cell Rep. 36, 109350 (2021). 5. E. A. Costa, K. Subramanian, J. Nunnari, J. S. Weissman, Science 359, 689–692 (2018). 6. M. Gamerdinger, M. A. Hanebuth, T. Frickey, E. Deuerling, Science 348, 201–207 (2015). 7. J. H. Lee et al., Proc. Natl. Acad. Sci. U.S.A. 115, E5487–E5496 (2018). 8. B. Wiedmann, H. Sakai, T. A. Davis, M. Wiedmann, Nature 370, 434–440 (1994). 9. M. del Alamo et al., PLOS Biol. 9, e1001100 (2011). 10. Y. Nyathi, M. R. Pool, J. Cell Biol. 210, 287–301 (2015).

We thank M. Leibundgut, T. Lenarcic, and M. Jaskolowski for discussions; R. Schloemer and E. Coellen for technical assistance; and S. Kreft for help with in vitro cysteine crosslinking experiments. Cryo-EM was collected at ScopeM at the ETH Zurich. We acknowledge the MRC - LMB Electron Microscopy Facility for access and support of electron microscopy sample preparation and data collection for NACTTC5-RNC and the Caenorhabditis Genetics Center for strains. Funding: This work was supported by the Swiss National Science Foundation (grant no. 310030B_163478); the National Center of Excellence in Research RNA & Disease Program of the SNSF (grant no. 51NF40_141735); a Roessler Prize, Ernst Jung Prize, and Otto Naegeli Prize for Medical Research (to N.B.); the German Science Foundation (grant nos. SFB969/A01 and A07 to E.D. and M.G.); the National Institutes of Health (grant no. R35 GM136321 to S.S.); the National Science Foundation (grant no. MCB-1929452 to S.-o.S); and the UK Medical Research Council (MRC grant MC_UP_A022_1007 to R.S.H.). V.C. was supported by V. Ramakrishnan, whose funding was from the MRC (grant no. MC_U105184332), the Wellcome Trust (grant no. WT096570), the Agouron Institute, and the Louis-Jeantet Foundation. We also acknowledge the support of the NVIDIA Corporation for the Titan Xp GPU through a grant awarded to A.J. Author contributions: A.J., M.G., H.-H.H., R.S.H., S.S., N.B., and E.D. conceived the project. A.J. and A.S. performed cryo-EM data collection for ER-targeting complexes containing NAC and SRP. A.J. determined the cryo-EM structures of NAC-RNC and NAC-SRP-RNC. M.G. and A.W. performed C. elegans in vivo and A.W. cross-linking experiments. H.-H.H. performed FRET titrations and single-molecule experiments. V.C. performed structural analysis of the NAC-TTC5-RNC. Z.U. characterized NAC cysteine variants. A.J., M.G., H.-H.H., S.S., E.D., and N.B. wrote the manuscript. All authors contributed to data analysis and the final version of the manuscript. Competing interests: The authors declare no competing interests. Data and materials availability: Cryo-EM maps and model coordinates are deposited in the EMDB as EMD-14191, EMD-14192, and EMD-14193 and in the PDB as PDB ID 7QWQ, 7QWR, and 7QWS for the NAC-SRP-RNCSS, NAC-RNCSS, and NAC-TTC5-RNCTUBB, respectively. All other data are available in the main text or the supplementary materials. SUPPLEMENTARY MATERIALS

science.org/doi/10.1126/science.abl6459 Materials and Methods Figs. S1 to S18 Tables S1 to S3 References (30–42) MDAR Reproducibility Checklist

27 July 2021; resubmitted 3 December 2021 Accepted 27 January 2022 10.1126/science.abl6459

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STRUCTURAL BIOLOGY

Dynamics and mechanism of a light-driven chloride pump Sandra Mous1, Guillaume Gotthard1,2, David Ehrenberg3, Saumik Sen4†, Tobias Weinert2, Philip J. M. Johnson5, Daniel James2‡, Karol Nass6, Antonia Furrer2, Demet Kekilli2§, Pikyee Ma2¶, Steffen Brünle2#, Cecilia Maria Casadei1,2, Isabelle Martiel7, Florian Dworkowski7, Dardan Gashi2,6, Petr Skopintsev2**, Maximilian Wranik2, Gregor Knopp6, Ezequiel Panepucci7, Valerie Panneels2, Claudio Cirelli6, Dmitry Ozerov8, Gebhard F. X. Schertler1,2, Meitian Wang7, Chris Milne6††, Joerg Standfuss2, Igor Schapiro4, Joachim Heberle3, Przemyslaw Nogly1* Chloride transport by microbial rhodopsins is an essential process for which molecular details such as the mechanisms that convert light energy to drive ion pumping and ensure the unidirectionality of the transport have remained elusive. We combined time-resolved serial crystallography with time-resolved spectroscopy and multiscale simulations to elucidate the molecular mechanism of a chloride-pumping rhodopsin and the structural dynamics throughout the transport cycle. We traced transient anion-binding sites, obtained evidence for how light energy is used in the pumping mechanism, and identified steric and electrostatic molecular gates ensuring unidirectional transport. An interaction with the p-electron system of the retinal supports transient chloride ion binding across a major bottleneck in the transport pathway. These results allow us to propose key mechanistic features enabling finely controlled chloride transport across the cell membrane in this light-powered chloride ion pump.

C

hloride transport is a fundamental process in biology, regulating osmotic pressure, cell growth, and membrane potential (1). In halophilic Archaea, inward halidepumping rhodopsins (halorhodopsin; HR) from Halobacterium salinarum (HsHR) and Natromonas pharaonis (NpHR) help to generate the membrane potential to produce ATP through the proton motive force, together with the outward proton-pumping bacteriorhodopsin (2–4). The role of halorhodopsin in marine bacteria, such as rhodopsin 3 from Nonlabens marinus (NmHR), remains unclear, but it has been speculated that these chloride pumps are involved in producing ATP and maintaining the osmotic balance of the cell (5). Ion gra-

1

Institute of Molecular Biology and Biophysics, Department of Biology, ETH Zürich, Zürich, Switzerland. 2Laboratory of Biomolecular Research, Biology and Chemistry Division, Paul Scherrer Institute, Villigen PSI, Switzerland. 3Experimental Molecular Biophysics, Department of Physics, Freie Universität Berlin, Berlin, Germany. 4Fritz Haber Center for Molecular Dynamics, Institute of Chemistry, The Hebrew University of Jerusalem, Jerusalem, Israel. 5Laboratory of Nonlinear Optics, Photon Science Division, Paul Scherrer Institute, Villigen PSI, Switzerland. 6Laboratory of Femtochemistry, Photon Science Division, Paul Scherrer Institute, Villigen PSI, Switzerland. 7 Laboratory for Macromolecules and Bioimaging, Photon Science Division, Paul Scherrer Institute, Villigen PSI, Switzerland. 8 Science IT, Paul Scherrer Institute, Villigen PSI, Switzerland. *Corresponding author. Email: [email protected] †Present address: Condensed Matter Theory Group, Laboratory for Theoretical and Computational Physics, Paul Scherrer Institute, CH5232 Villigen PSI, Switzerland. ‡Present address: Department of Physics, Utah Valley University, Orem, UT 84058, USA. §Present address: Celerion Switzerland AG, CH-8320 Fehraltorf, Switzerland. ¶Present address: Virometix AG, CH-8952 Schlieren, Switzerland. #Present address: Leiden Institute of Chemistry, Leiden University, 2333 CC Leiden, The Netherlands. **Present address: California Institute for Quantitative Biosciences (QB3), University of California, Berkeley, Berkeley, CA, USA. ††Present address: European XFEL GmbH, 22869 Schenefeld, Germany.

SCIENCE science.org

dients are also involved in the generation and propagation of neuronal signals, which has enabled the application of these photoactive chloride-pumping rhodopsins as optogenetic tools in the control of neuronal activity (6). Chloride-pumping rhodopsins bind a retinal chromophore in all-trans configuration, which, upon photoisomerization, initiates the transport cycle (fig. S1) through a mechanism that is still not well understood. The main transport events can be described following a modified Jardetzky alternate access model (7) in which a high-affinity substrate-binding site is transformed into a low-affinity site with light-induced structural changes enabling access to the cytoplasmic release pathway (fig. S2). The first structure of a halide-pumping rhodopsin from halophilic Archaea was reported 20 years ago (8), revealing a chloride-binding site close to the protonated Schiff base (PSB) of the retinal. However, it is essential to determine transient chloride-binding sites to decipher details of the ion transport mechanism. These remained elusive, except for one transient site that was identified in cryo-trapped photointermediate states of the archaeal halorhodopsins HsHR (9) and NpHR (10). Recently, the resting structure of the chloride pump NmHR from marine bacteria was published (11, 12). Although the latter shares only 21% sequence identity with HsHR and NpHR, it is conceivable that these structurally similar proteins may use comparable elements in their transport mechanism. Similarities are also evident in the photocycle. The classical bacteriorhodopsin photocycle is usually described by the following scheme: dark + hn → K→ L → M→ N → O → dark. Halorhodopsins do not display the M state intermediate, indicating the lack

of a PSB deprotonation stage [for a detailed photocycle comparison, see fig. S3 (13–17)]. Understanding the molecular mechanism of ion transport requires a methodology with near-atomic spatial resolution and up to picosecond temporal resolution (13, 15, 18–26). Recent years have witnessed rapid development in the field of time-resolved serial femtosecond crystallography (TR-SFX) at x-ray free electron laser (XFEL) facilities with a similar strategy adapted to synchrotrons: time-resolved serial synchrotron crystallography (TR-SSX). The ability to photoactivate rhodopsins renders NmHR an ideal target for time-resolved pump-probe experiments to elucidate the structural dynamics of chloride transport. The ion transport in halorhodopsin contrasts in charge and direction with the studied with TR-SFX bacteriorhodopsin (13, 23, 25) and the sodium-pumping rhodopsin Krokinobacter eikastus rhodopsin 2 [KR2 (15)], thus presenting an interesting opportunity for mechanistic comparison of transport strategies in nature. In this work, we used an approach based on the detection of anomalous signals in the photostationary state using the serial crystallography method to identify transient anionbinding sites inside NmHR. In addition, to provide a comprehensive view of the anion transport mechanism in NmHR, structural intermediates from Dt = 10 ps until 50 ms were determined using a combination of TR-SFX and TR-SSX for resolving structural intermediates of the early and late photocycle, respectively. Our structural data were complemented with crystal spectroscopy and hybrid quantum mechanics/molecular mechanics (QM/MM) simulations. The time-resolved crystallography experiments allowed us to describe two molecular gates orchestrating the unidirectional chloride transport and analyze the mechanism of light energy utilization in transport initiation proceeding through an interaction of the retinal p-electron system with the chloride. Results and discussion Tracing the chloride transport pathway

A chloride-binding site named Cl351 was identified on the extracellular side of the retinalbinding pocket in the resting state of NmHR (11, 12) (fig. S4C). Chloride transport to the cytoplasm would thus require transfer across the retinal. The presence of such an early transport bottleneck ensures tight light control, enabling transport only upon photoactivation. The resting-state structure of NmHR revealed three water cavities formed by conserved residues (fig. S4, A and B, and S5) that may be involved in the transport pathway. However, a prominent tunnel that would allow for the passage of the anion was not identified. Previous biochemical studies showed that NmHR can transport (5) and bind bromide with a 25 FEBRUARY 2022 • VOL 375 ISSUE 6583

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similar affinity as chloride [Cl–: Kd = 24 mM; Br–: Kd = 10 mM (17)]. Furthermore, structural studies show that a bromide ion is coordinated by the retinal PSB in the resting-state Br351-binding site (11). We have assumed that bromide can mimic the transport pathway of chloride ions. Therefore, to detect transient anion-binding sites across the protein, we replaced chloride with bromide, which can be localized by anomalous dispersion in x-ray diffraction. Bromide-soaked crystals were continuously illuminated with a 520-nm laser diode while being delivered for serial crystallographic data collection at the Swiss Light Source (26). Perpetually activating NmHR within the crystals results in a photostationary state with a mixture of photocycle intermediates (Fig. 1B)

and partial occupancies of possible anionbinding sites. However, the O spectroscopic intermediate was predominantly accumulated (fig. S6). Molecular replacement combined with single-wavelength anomalous dispersion enabled us to identify four intramolecular sites overlapping with internal water molecules (Fig. 1A, all scatterers listed in fig. S7, and tables S1 and S2): one corresponding to the resting state (Br351), one in a hydrophilic cavity on the cytoplasmic half of the protein (Br353), and two in hydrophilic cavities in the extracellular half of the protein (Br354 and Br355). To complement the steady-state experiments and to resolve the structural intermediates of the consecutive steps of transport, we collected time-resolved serial crystallography data. Time

Fig. 1. Halide-binding sites and photocycle of NmHR. (A) Ribbon model of NmHR showing the overall secondary structure. Locations of bromide-binding sites, as determined by anomalous scattering, are shown as brown spheres. (B) Schematic representation of the NmHR photocycle with the corresponding absorption maxima. (C) Two-dimensional representation of transient UV/Vis absorption experiments of NmHR crystals after pulsed photoexcitation. Negative absorption changes (blue areas) correspond to the depletion of ground-state NmHR and positive absorption (red areas) to the rise of intermediate states. (D) Kinetic data 846

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delays from picoseconds to microseconds were recorded at the SwissFEL X-ray Free Electron Laser (27) and complemented with millisecond data from the Swiss Light Source synchrotron (26) (fig. S8). As discussed in the following sections, the time-resolved crystallography experiments allowed the temporal assignment of the transient binding sites identified in the photostationary state. NmHR photocycle in crystals

NmHR was crystallized in a lipidic cubic phase that mimics the amphipathic environment of cellular membranes. Nevertheless, crystal contacts and crystallization conditions may influence protein kinetics in the crystalline state

from time-resolved IR spectroscopy on the crystals. (E) Data in (C) and (D) have been subjected to global fit analysis by applying a model of sequential intermediate states. The analysis yielded the concentration profiles of the intermediate states, which were four states for the UV/Vis data (blue traces) and three states for the IR data (red traces), assigned to a mixture of the spectroscopic K/L state, the O1 state, the O2 state, and NmHR′ (for which a signal was only observed in the UV/Vis data). The dashed vertical lines indicate the relative concentrations of intermediate states at delay times applied in the SFX experiments. science.org SCIENCE

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(28). We therefore probed the rise and decay of spectroscopic states (Fig. 1B) in crystals by time-resolved absorption spectroscopy in the infrared (IR) and in the ultraviolet/visible (UV/ Vis) region (Fig. 1, C and D). In the nanoseconds to early microseconds, we observed a mixture of K (with lmax at 610 nm) and L intermediates (with lmax at 540 nm; table S3). The L intermediate decays into a red-shifted O intermediate (lmax at 610 nm), which is predominant in the late microseconds until milliseconds

(Fig. 1E). The photocycle of NmHR probed in solution (17) indicated the rise of the early O1 to be accompanied by chloride release and the decay of the subsequent O2 state to be limited by chloride uptake. Compared with NmHR in solution, the kinetics in the crystalline state are slightly altered with a faster decay rate of the spectroscopic intermediates up to the O1 state and a slower decay rate of the O2 state. These changes, however, can also be attributed to an increased chloride concentration (17).

Fig. 2. NmHR activation and initiation of transport. (A) Chloride ion–binding site in the resting state and its evolution in the early active states. In the presence of photoisomerized retinal at Dt = 10 ps, when the spectroscopic K intermediate is accumulated, the Cl351 is shifted away from the PSB. At Dt = 1 ms, when a mixture of the K and L spectroscopic intermediates is accumulated, an additional Cl352-binding site forms in the proximity of the PSB. Difference Fourier electron density (Flight – Fdark) contoured at 3.0 s is shown as a blue (positive) mesh and a golden (negative) mesh. The corresponding extrapolated electron density maps can be found in figs. S11 and S12. The chloride ion is depicted as green sphere; the C atom sticks are colored gray (resting state) and pink (active states; Dt = 1 ms conformation B in dark purple). At Dt = 20 ms, when the O1 spectroscopic intermediate is accumulated, the anion has passed over the retinal chromophore SCIENCE science.org

NmHR activation

Light-driven ion transport by microbial rhodopsins is initiated by the all-trans to 13-cis photoisomerization of the retinal chromophore. Time-resolved difference Fourier maps (Fo(10ps) – Fo(dark)) of our fastest TR-SFX time delay at Dt = 10 ps show that the retinal has isomerized (Fig. 2A and fig. S9). Structural refinement results in a nearly planar 13-cis configuration, however, the chromophore is tilted by 17° compared with the all-trans-retinal of the resting state (fig. S10, A

and the resting-state Cl351-binding site has been depleted. (B) Schematic overview of the PSB flipping dipole (Dt = 10 ps), dragging the chloride over the retinal chromophore (Dt = 1 ms). (C) Molecular electrostatic potential surface of the retinal chromophore (with the nitrogen of the PSB shown as a blue sphere) and Cl352 (green sphere) of the 1-ms intermediate. The isocontour value of the surface is 0.005 e Bohr−3. Blue and yellow colors correspond to regions of positive and negative electrostatic potential (in atomic units), respectively. Comparison with absent chloride is provided in fig. S15. (D) Absorption maxima of the resting state and the photocycle intermediates (excitation energy DE, in nanometers) as determined by QM/MM simulations and UV/Vis spectroscopy. The calculated values are consistently blue shifted, including the reference resting state. More details can be found in tables S6 and S7. 25 FEBRUARY 2022 • VOL 375 ISSUE 6583

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to C). The C20 methyl group of the isomerized retinal pushes against Trp201, shifting it away by 0.4 Å. Trp99 shifts by 0.3 Å toward 13-cisretinal, filling in the newly created space (fig. S11). The geometry of 13-cis-retinal resembles more closely that observed for sodium-pumping rhodopsin KR2 than that of bacteriorhodopsin (fig. S10D). The PSB changes its orientation upon retinal isomerization. In the resting state, the proton of the PSB points toward the extracellular side and forms an H bond with Cl351 (Cl351-PSB distance: 3.1 Å; Fig. 2, A and B). At Dt = 10 ps, the PSB flips, with its proton pointing toward the cytoplasm. Cl351 shifts away from the PSB, increasing the distance to 4.1 Å and breaking the H bond between the anion and the PSB, resulting in a destabilization of this binding site. Our QM/MM simulations indicate that 28.2 kcal mol−1 of energy is stored upon charge separation between the PSB and Cl351 at Dt = 10 ps. This energy corresponds to more than half of a green light photon (530 nm or 53.9 kcal mol−1) to drive the subsequent reactions. Here, the stored energy is attributed to the photon energy that remains in the protein after the isomerization and subsequent return to the ground state. It is calculated as the difference between the resting state of NmHR and the K intermediate. A recent study complements our results, describing the ultrafast structural changes in NmHR preceding chloride transport, including the retinal geometry evolution during the isomerization (29). Our 10-ps time delay provides a single time point overlap with the pre-

vious study, which shows overall agreement of the early structural changes. First step of chloride transport

Upon depletion of the Cl351 site observed at Dt = 1 ms (Fig. 2A), we noted a positive difference density between the retinal PSB and Thr102. We modeled it as chloride Cl352 in an alternate position to the still partially occupied Cl351 site (fig. S12). The partially formed Cl352-binding site is stabilized by interactions with the retinal PSB (3.1 Å to Nz), the p system (3.1 Å to C14 and C15 of the retinal), and the newly adopted 80° rotamer of Thr102 (2.5 Å to Og). We analyzed these interactions using quantum-chemical calculations and found that the stabilization is dominated by the electrostatic component between chloride and PSB (table S4). In addition, we have found a contribution from the C14– C15=N fragment of the retinal (fig. S13 and table S5). We identified an anion-p interaction between the conjugated p system of the retinal and Cl352 in which the negative charge of the anion polarizes the p-electron density of the chromophore (fig. S14). The polarization resembles the common interaction between anions and p electrons of aromatic rings (30–35). The polarization effect of the anion is also evident from the electrostatic potential maps of the retinal PSB in the presence of the chloride anion, with a negative potential extending up to the b-ionone ring of the retinal (Fig. 2C and fig. S15). Further validation stems from the calculated QM/MM excitation energy, which is in quantitative agreement with the experimental counterpart obtained from spectros-

Fig. 3. Steric gate prevents chloride backflow. (A) Straightening of helix C at Dt = 20 ms to 7.5 ms, during which the spectroscopic O intermediates are accumulated, allows Asn98 to enter the resting-state chloride-binding site (intermediate Dt = 1 ms conformation A with the Cl351-binding site shown in gray, intermediate Dt = 2.5 ms with a straightened helix C shown as pink sticks). The straightening of helix C is stabilized by the formation of a hydrogen bond between the backbone carbonyl group of Asn98 and the Thr102 side chain, shown by dashed lines with the distance measured in angstroms. (B) Two cylinders are fitted, from Asn92 to Asn98 and from Asn98 848

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copy (Fig. 2D and tables S6 and S7). The red shift of the 1-ms intermediate with the anion in the Cl352-binding site with respect to the resting state is 4 nm for the QM/MM simulation and 5 nm for the spectroscopic measurement. By contrast, when Cl352 is omitted or replaced by a water molecule, the computed shift is 164 or 187 nm, respectively. On the basis of the archaeal HsHR restingstate structure (8), it was hypothesized that the anion could be “dragged” by the moving PSB, but the passage across the retinal remained unknown. Our NmHR data provide experimental evidence that, upon charge separation between photoisomerized retinal and Cl351 (leading to 28.2 kcal mol−1 of stored energy), the anion follows the PSB in microseconds, creating a pathway between the retinal and helix C. The identified anion-p interaction appears to be an essential step in the transport process. The first step of the chloride transport brings the anion 4.0 Å closer toward the cytoplasm. Steric molecular gate

In the resting state, helix C exhibits a kink next to Cl351 [Fig. 3, B and C (36)]. Upon depletion of Cl351, the kink on helix C relaxes from 38° ± 6° in the resting state to 22° ± 7° in the structure at Dt = 20 ms after light excitation. The kink relaxes even further, reaching a minimum angle of 16° ± 7° at Dt = 2.5 ms. A shift of helix C was also observed in active states of the homologous sodium-pumping rhodopsin KR2 (15). However, the observed changes do not lead to kink formation (fig. S16). We may infer

to Pro104, from which the kink angle at Asn98 can be calculated (36). The fitted cylinders and calculated angle are shown for the Dt = 1 ms and Dt = 2.5 ms. (C) Change in the helix C kink angle over time, calculated using KinkFinder (36). One should consider that the apparent linear motion of the helix may be a result of changes in the populations of the intermediates. Error bars indicate the heuristically determined 95% confidence interval of the calculated kink angle (36). The blue line indicates the kink angle determined for the resting-state structure of 38.1°, with an estimated error of ± 6.3° represented in light blue. science.org SCIENCE

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that an intermediate state with sodium captured between retinal and helix C could lead to similar kink formation in KR2. In NmHR, the relaxation of the kink moves the side chain of Asn98 into the chloride-free Cl351 site. This movement is rationalized as a sterically closing molecular gate preventing reverse flow of chloride. The Asn98 side chain, while replacing Cl351, interacts only with the waters Wat484 (3.1 Å) and Wat407 (3.5 Å). Additional stabilization of this closed steric molecular gate is achieved by a new H bond between Thr102 and the carbonyl group of the Asn98 backbone (Fig. 3A), which seals the gate. Thr102, which is part of the conserved NTQ motif defining the rhodopsin family to which NmHR belongs (fig. S5), seems to play multiple roles in the early transport stages. In the resting state, it coordinates Cl351, whereas at Dt = 1 ms, the Thr102 side chain assists in transferring the chloride to the Cl352 position by rotamerization. Finally, Thr102 seals the molecular gate, preventing chloride backflow from Dt = 20 ms once the anion is on its way toward the cytoplasm. The equivalent residue in sodiumpumping rhodopsin KR2 is Asp116, which provides an electrostatic driving force for the cation and neutralizes the positive charge of the PSB (15), demonstrating substantial evolutionary adaptation of rhodopsins to different substrates. Chloride release through Gln109 of the NTQ motif

At Dt = 20 ms, the Cl351- and Cl352-binding sites are depleted, and the Cl353 may emerge above

the retinal by replacing Wat485, which adds another 14 Å distance toward the cytoplasm on the transport pathway (Fig. 4A). The proposed transient Cl353-binding site is characterized by a positive peak in Fo(20ms) – Fo(dark) and displays an anomalous signal in the Brsoaked 13.7 keV photostationary SSX data (Fig. 1A). It should be noted that the anomalous difference density peak for the transient Cl353binding site is of limited strength (table S1 and fig. S7), likely because of the low occupancy of the transient binding site in the photostationary state. The Cl353-binding site is accessed through Wat401 and Wat402 and formed by Gln109 of the conserved NTQ motif, Ser54 and Thr243 (Fig. 4A). We also observed a weak anomalous signal between Wat402 and Leu106 in the photostationary data (table S1). However, the site could not be modeled in our TR-SFX data. A conformational change of the residue corresponding to Leu106 (Ile134) is needed to form a transient chloride-binding site in the NpHR structure of the N intermediate (10). Gln109 of NmHR is found at a strategic position for ion pumps. The equivalent residue of outward proton-pumping bacteriorhodopsin is Asp96, which is the internal proton donor to the retinal Schiff base (26). In KR2, the equivalent residue is Gln123, which is involved in the outward transport of sodium (15). These analogies suggest that pumping rhodopsins share sections of the transport pathway despite the different charge and size of the translocated ion and even in cases of opposite ion flow.

Fig. 4. Chloride transport and release. (A) A new chloride-binding site is identified after the anion is transferred over the retinal chromophore in the light-activated intermediate at Dt = 20 ms. Dashed lines indicate hydrogen-bonding interactions in the Cl353-binding pocket with measurements in angstroms. Difference Fourier electron density [Fobs(20 ms) – Fobs(dark)] contoured at 3.0 s is shown as a blue (positive) mesh and a golden (negative) mesh. (B) Exit site at Dt = 20 ms. Conformation B of the Thr51 side chain is shown as purple sticks. The panel on the right shows a magnified SCIENCE science.org

In the final stage, chloride is possibly released through the Wat482-binding site on the surface, which is formed at Dt = 300 ms and within 8 Å from Cl353 (Fig. 4, B to D). It is accompanied by ordering of Thr51 and a rotameric change of Ser40, both pointing toward Wat482. Chloride uptake

NmHR appears to form an electric dipole (Fig. 5A) with the extracellular surface of predominantly negative charge and the cytoplasmic surface of predominantly positive charge. The resulting dipole moment presents an additional driving force for charge transport across the cell membrane, rendering directionality to those transitions that rely on passive anion diffusion. The net negative charge on the extracellular solvent accessible surface creates a barrier for anion uptake (Fig. 5A), the exception being a water cavity enclosed by Asn3 (Fig. 5B). The anion entry into this cavity is driven by the positive charge of conserved Arg223. We identified an anomalous site in the photostationary SSX data and a positive peak in the Fo(20ms) – Fo(dark) map of the TR-SFX experiments, which we modeled as Cl354 (Fig. 1A and fig. S17). The latter is coordinated by Arg223, Tyr96, Wat403, and Wat404. Passing of the chloride further toward the retinal is facilitated by the positive charge of the conserved Arg95, likely through Wat429 (fig. S18A). To enter another water cavity consisting of Wat409 and Wat416 (from Dt = 1 ms, additionally Wat481; fig. S19), the anion needs to pass Gln68, where we observed a rotamer change only

view of the exit site with the extrapolated electron density (2Fex – Fcalc) as a blue mesh at 1.0 s (carved at 1.8 Å from the side chains). (C) At Dt = 300 ms, the residue Ser40 changes conformation, whereas Thr51 adopts a single conformation to bind Wat482 (shown as a red sphere), which is only observed from Dt = 300 ms to 2.5 ms. At the same time, Cl353 and Wat485 are both absent at Dt = 300 ms. (D) Mapping the electrostatic potential (at ± 5 kT/e) on the solvent-accessible surface shows that the exit site is surrounded by a positive electrostatic potential. 25 FEBRUARY 2022 • VOL 375 ISSUE 6583

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Fig. 5. Chloride uptake and electrostatic gate. (A) Ribbon model of NmHR with surface electrostatics shown as an electrostatic potential isocontour at ±1 kT/e, with positive potential shown in blue and negative in red. (B) Solventaccessible surface near the proposed chloride entrance site, with the electrostatic potential projected on the surface at ±3 kT/e. (C) Evolution of the accessibility to the retinal-binding pocket at Dt = 12.5 to 45 ms. The lightactivated conformations are shown as light pink sticks overlaid on the resting-state

at Dt = 12.5 ms (fig. S18B). Once the halide diffuses into the Wat409 position, the transport pathway is occluded by Asp231 (Fig. 5C and fig. S20). Electrostatic gate enables recharging of the resting state

We calculated the excitation energy for different protonation states of Asp231 using hybrid QM/MM simulations to determine the form in which it is present. Only the anionic form of Asp231 results in the excitation energy consistent with the experimental value (table S8). Along with an interaction distance of 2.9 Å, it supports the presence of a salt bridge between Asp231 and Arg95. We propose that after diffusion into the Wat409 position, the halide interferes with the electrostatic attraction between Arg95 and Asp231 (Fig. 5C). We observed that the conformation of the side chain of Asp231 rotates from Dt = 22.5 to 37.5 ms, thereby interacting with the nearby His29 instead of Arg95 (Fig. 5, C and D). This opens the electrostatic gate and creates a pathway for the halide to the Cl355-binding site, a convenient position for recharging of the Cl351 site 4 Å away. Before recovery of the resting state, the electrostatic gate closes again, preventing anion leakage back into the bulk solvent. In this way, the electrostatic gate ensures vectorial transport. 850

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structure shown as transparent gray sticks. The electrostatic potential isocontour at ±3 kT/e is shown around the Arg95 and Asp231 side chains. See fig. S20 for the corresponding electron densities. (D) Schematic representation of the electrostatic gate. As the chloride ion approaches residues Asp231 and Arg95 (step 1), the charge interaction between the residues is shielded, allowing Asp231 to interact with His29 instead (step 2). This creates a pathway for chloride to proceed toward the resting-state binding site (step 3).

From Dt = 12.5 ms, the kink angle in helix C increases again (likely due to a shift in the populations of intermediates) until ~Dt = 45 ms, where helix C resembles the resting-state conformation (Fig. 3C). With the shift of helix C, the side chain of Asn98 also leaves the Cl351 site, and the retinal isomerizes back to all-trans configuration. It is plausible that the chloride pushes the side chain of Asn98 aside and breaks the steric gate seal driven by the energy gained from a strong electrostatic interaction with PSB. Conclusions

We have traced several possible transient anion-binding sites buried inside NmHR, allowing us to propose the chloride transport pathway (summarized in fig. S21 and movie S1). The time-resolved experiments enabled us to describe in atomic detail how the photonic energy absorbed by the retinal is stored in the form of charge separation between the isomerized retinal and its chloride counterion. In the early microseconds after protein activation, this excess energy drives the very first step of anion transport through an anion-p interaction. Comparing our results with the insights from previous TR-SFX studies of lightdriven ion pumps (13, 15), it becomes clear that rhodopsin pumps with different substrate af-

finities adopt diverse strategies to overcome the retinal bottleneck in ion transport. Whereas in bacteriorhodopsin and KR2, deprotonation of the Schiff base by the counterion (Asp85 and Asp116, respectively) is required for successful transport, in NmHR, no residue side chain acts as the proton acceptor, and the positively charged PSB drives the transfer of the anion over the chromophore. In the steps after the initiation of anion transport, we propose that the steric molecular gate closes over the original anion-binding site accompanied by relaxation of helix C, which finally prevents a backflow. Anion release in the late microseconds is diffusion driven and assisted by the macroscopic dipole moment across the membrane created by the negative extracellular and positive cytoplasmic surface charges. The exit side to cytoplasm that we propose in this work aligns with the suggested ion selectivity filter in KR2 (37, 38). On the extracellular side, the anion uptake is likely guided by a positive patch in the otherwise negatively charged protein surface. The transient sodium release site in KR2 identified at Dt = 20 ms and created by a shift of the Arg243 (15) is located 5 Å away from the transient Cl354-binding site in the triple water cluster (coordinated by the corresponding Arg223) science.org SCIENCE

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of NmHR (fig. S22D), indicating that the sodium and chloride transport pathways may partially overlap on the extracellular side of the protein. Through consecutive steps driven by the charge of two arginine residues, the halide is proposed to arrive at an electrostatic molecular gate, a bottleneck in the anion uptake pathway. The gate likely opens upon interaction with the negative charge, allowing the anion to access the retinal-binding pocket. The subsequent closure of the electrostatic gate prevents anion backflow, imparting a directionality that is a characteristic feature of ion pumps. The counterparts of Arg95 and Asp231 forming the electrostatic gate in bacteriorhodopsin (Asp212 and Arg82) play important functional roles as part of the complex counterion of the retinal and in the proton transfer pathway (13). When comparing the proposed anion transport pathway of NmHR with available archaeal HR structures, it becomes apparent that the anion-binding site coordinated by Gln105 identified in the HsHR resting state (Asn92 in NmHR) (9, 39) does not align with the anion uptake pathway in NmHR. Although in HsHR, this anion-binding site is directly accessible from the bulk solvent, in NmHR, the site is occluded from solvent by the extended N terminus and the different position of the B-C loop (fig. S22B). Conversely, the anion-binding site in the NpHR N state (10) is located over the retinal and in the proximity of Ile134 (Leu106 in NmHR), ~4 Å away from Cl352 in NmHR, indicating a plausible pathway toward the Cl353 site (fig. S22C). In addition, we observed how retinal isomerization increases the affinity for the anion in the transient Cl352-binding site, allowing access to the cytoplasmic half of the protein and driving ion transfer (40–42); however, we have not found a clear conformational change switching the accessibility of the exit and uptake tunnel in the late photocycle, as has been proposed for NpHR (10, 16). Although differences in the ion transport mechanism of archaeal and bacterial halorhodopsins may exist, the chloride pumps also share many commonalities. The large conformational changes in helix C of NpHR in the anion-free (O-like) state (10, 43) and the existence of a salt bridge next to the resting-state chloride-binding site of the archaeal HsHR and NpHR (8, 44) suggest that the molecular gates may be a general feature of halorhodopsin ion pumps. In summary, we have proposed the ion transfer pathway in bacterial halorhodopsin and discussed the interplay between the driving force created by the protein dipole moment and the control of transport by molecular gates. Furthermore, we have provided details about how light energy is converted into kinetic energy for chloride translocation. The resulting charge separation represents a fundamental SCIENCE science.org

feature for light energy conversion in nature as well as in technology. RE FERENCES AND NOTES

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AC KNOWLED GME NTS

We thank the Macromolecular Crystallography group for support during the testing of crystals at the Swiss Light Source and the access and support of the Crystallization Facility at Swiss Light Source; the Paul Scherrer Institute, Villigen, Switzerland, for provision of XFEL and synchrotron radiation beamtime at beamlines X06SA (PXI) of the Swiss Light Source and Alvra at SwissFEL; everybody involved in ensuring the smooth operation of the SwissFEL X-ray Free Electron Laser and Swiss Light Source during our experiments; and F. Allain, S. Jonas, and A. Gossert for access to the office, laboratory space, and equipment at L floor of HPP building of ETH Zurich and for the supportive working environment provided. Funding: This work was supported by the Swiss National Science Foundation (Ambizione grant PZ00P3_174169 to P.N.; project grant 31003A_179351 to J.S.; and project grant 310030B_173335 to G.F.X.S.); the National Centre of Competence in Research: Molecular Ultrafast Science and Technology (C.M. and J.S.); the German Research Foundation via SFB 1078, projects B3 (J.H.), C6 (I.S.) and via EXC 2008/1 UniSysCat 390540038 (J.H.); Holcim Stiftung (P.M.); European Union’s Horizon 2020 research and innovation program (Marie-Sklodowska-Curie grant agreements 701646 and 701647 to G.G., D.K., and S.B.); and the European Research Council (ERC) European Union’s Horizon 2020 research and innovation program (grant 678169 ‘PhotoMutant’ to I.S.). Author contributions: P.N. designed and coordinated the project. I.S. and S.S. coordinated quantum chemical calculations. C.M. coordinated the pump-probe experiments at the Alvra endstation. J.H. coordinated time-resolved spectroscopy. G.F.X.S. coordinated and supported crystallographic applications at SwissFEL and contributed to discussions throughout the project. S.M. expressed, purified, and crystallized NmHR. S.M., A.F., D.K., and P.M. secured a constant supply of sample during the SFX beamtime. S.M. and D.J. optimized crystal injection. D.J., G.G., F.D., I.M., D.G., and P.S. operated and aligned the lipidic cubic phase injector during the beamtime. P.J., M.J., K.N., G.K., C.C., C.A., M.J., and C.M. aligned and operated the endstation, including the laser system, and designed the Alvra prime pump-probe station. D.O. and K.N. built and operated the SFX data analysis pipeline. T.W., C.M.C., and S.B. performed data processing during the beamtime. S.B., J.S., V.P., and M.W. recorded progress during data collection. J.S. supported P.N. in coordination of the experiment at SwissFEL. S.M. and P.N. optimized data processing. S.M., G.G., and P.N. refined and interpreted structures. S.S. and I.S. performed quantum-chemical calculations. D.E. and S.M. performed the time-resolved spectroscopic experiments and interpreted them together with J.H. E.P. synchronized diode and detector triggering at the synchrotron. D.J., F.D., and T.W. built the pump-probe setup at the synchrotron. S.M., G.G., P.N., and D.J. collected synchrotron data with suggestions on anomalous data collection and analysis from T.W. P.N. wrote the manuscript with direct contributions from S.M., G.G., D.E., J.H., S.S., and I.S. with further suggestions from most of the other authors. All authors read and approved the manuscript. Competing interests: The authors declare no competing interests. Data and materials availability: Resting-state coordinates and structure factors have been deposited in the PDB database under accession codes 7O8F (SFX), 7O8L (SSX), and 7O8Y (13.7 keV anomalous data). For the light-activated datasets, coordinates, light amplitudes, dark amplitudes, and extrapolated structure factors have been deposited in the PDB database under accession codes 7O8G (10 ps), 7O8H (10 ns), 7O8I (1 ms), 7O8J (20 ms), 7O8K (300 ms), 7O8M (2.5 ms), 7O8N (7.5 ms), 7O8O (12.5 ms), 7O8P (17.5 ms), 7O8Q (22.5 ms), 7O8R (27.5 ms), 7O8S (32.5 ms), 7O8T (37.5 ms), 7O8U (45 ms), 7O8V (55 ms), and 7O8Z (photostationary; 13.7 keV anomalous data). SFX raw data (45), SSX raw data (46), and 13.7 keV anomalous data (47) are available at the PSI Public Data Repository. SUPPLEMENTARY MATERIALS

science.org/doi/10.1126/science.abj6663 Materials and Methods Supplementary Text S1 to S3 Figs. S1 to S29 Tables S1 to S13 References (48Ð81) Movie S1 MDAR Reproducibility Checklist

29 May 2021; accepted 26 January 2022 Published online 3 February 2022 10.1126/science.abj6663

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NANOMATERIALS

Highly stretchable van der Waals thin films for adaptable and breathable electronic membranes Zhuocheng Yan1, Dong Xu2, Zhaoyang Lin1, Peiqi Wang1, Bocheng Cao1, Huaying Ren1, Frank Song1, Chengzhang Wan1, Laiyuan Wang2, Jingxuan Zhou2, Xun Zhao3, Jun Chen3, Yu Huang2,4*, Xiangfeng Duan1,4* The conformal integration of electronic systems with irregular, soft objects is essential for many emerging technologies. We report the design of van der Waals thin films consisting of staggered two-dimensional nanosheets with bond-free van der Waals interfaces. The films feature sliding and rotation degrees of freedom among the staggered nanosheets to ensure mechanical stretchability and malleability, as well as a percolating network of nanochannels to endow permeability and breathability. With an excellent mechanical match to soft biological tissues, the freestanding films can naturally adapt to local surface topographies and seamlessly merge with living organisms with highly conformal interfaces, rendering living organisms with electronic functions, including leaf-gate and skin-gate transistors. On-skin transistors allow high-fidelity monitoring and local amplification of skin potentials and electrophysiological signals.

T

he integration of electronic systems with irregular, soft objects is of increasing importance for many emerging technologies, including electronics for the Internet of Things and bioelectronics for monitoring dynamic living organisms and for diagnosing and treating human diseases in the context of personalized medicine and telehealth (1). A robust bioelectronic system requires intimate interaction with biological structures to perform specific operations, such as biological signal recording (2–4), amplification (5–7), and extraction (8), as well as delivering electrical (9, 10) or chemical stimulation (11). Thus, the implementation of bioelectronics hinges on a number of unusual material and device characteristics, including electronic performance; mechanical flexibility, stretchability, or malleability to ensure conformal and adaptable interfaces with dynamically evolving microscopic surface topographies; and permeability or breathability for gas and/or nutrient exchange between living organisms and their surroundings to lessen perturbation of natural biofunctions. Conventional hard electronic materials exhibit an intrinsic mismatch with soft biological tissues in terms of electrical conductivity, mechanical response, permeability, and environmental adaptability. Hard inorganic semiconductors can be made flexible in an ultrathin membrane format but are barely stretchable and cannot form a conformal interface with

1

Department of Chemistry and Biochemistry, University of California, Los Angeles, CA 90095, USA. 2Department of Materials Science and Engineering, University of California, Los Angeles, CA 90095, USA. 3Department of Bioengineering, University of California, Los Angeles, CA 90095, USA. 4California NanoSystems Institute, University of California, Los Angeles, CA 90095, USA.

*Corresponding author. Email: [email protected] (X.D.); [email protected] (Y.H.)

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irregular geometries with nonzero Gaussian curvatures owing to their fundamental topological limitations (12). The development of specifically designed deformation-tolerant structures, such as wrinkled (13), buckled (14), waved (15), or serpentine structures (16–18), bring macroscopic stretchability but not microscopic conformability, because of the intrinsic microscopic structural undulation. Organic or composite semiconductor thin films can be made stretchable or conformal (19) but usually exhibit insufficient electronic performance (12, 20) or limited stability in a typical wet biological environment. Additionally, traditional inorganic membranes or organic thin films typically exhibit limited mechanical robustness in the ultrathin freestanding format and require a polymer [e.g., polydimethylsiloxane (PDMS) and polyimide (PI)] substrate support to retain structural integrity (12) and specific porous architecture design to achieve breathability (21). The polymer substrate is typically much thicker (≫1 mm) than a cell membrane (~10 nm), with a large bending stiffness (22) and poor conformability and adaptability to the dynamically evolving biological structures (23). Inspired by van der Waals (VDW) interactions in biological assemblies, we exploited these interactions to assemble two-dimensional (2D) nanosheets (24–27) into freestanding VDW thin films (VDWTFs) with an excellent mechanical match to soft biological tissues that can directly adapt to and merge with living organisms with ultraconformal and breathable membrane–tissue interfaces. The VDWTFs feature bond-free VDW interfaces between the staggered 2D nanosheets, opening sliding and rotation degrees of freedom between neighboring nanosheets to endow unusual mechanical flexibility, stretchability, and malleability. The staggered VDWTFs also feature

a percolating network of nanochannels for permeability or breathability. Topological and mechanical limitations of a conformal interface

Although the flexibility of intrinsically stiff materials (e.g., a silicon wafer or hard cardboard) can be increased in the ultrathin membrane format (e.g., a silicon membrane or paper) (28), stretchability is fundamentally limited by the covalent chemical bonds and barely changes with reduced thickness (29). Owing to intrinsic topological limitations, it is impossible to use such flexible yet unstretchable membranes to make a conformal interface with local topographies with nonzero Gaussian curvatures (e.g., wrapping a piece of paper around a pen; Fig. 1A) (30). To achieve a conformal interface with irregular geometries, stretchability is essential to allow necessary deformation to adapt to the local surface topographies. Specific polymeric materials with intermolecular slippages between polymer chains can be made stretchable (31, 32) and adaptable to local topographies under sufficient tensile stress (e.g., wrapping parafilm around a pen; Fig. 1B) (29). To achieve a conformal interface with a stretchable membrane, external pressure is needed to induce sufficient deformation to match the local surface topography, which results in a contact pressure that can cause tissue deformation or damage (e.g., tightly wrapping parafilm around a fingertip). A 3D geometric model is constructed to visualize the conformal adapting process of a stretchable membrane on spherical topographies and to explore the evolution of the local deformation with the contact pressure (Fig. 1C). With increasing load, the membrane gradually adapts to the spherical indentations, with the membrane grid stretched and expanded to accommodate the local strain and deformation during the conformal adapting process. We use a simplified spherical indentation model to evaluate the maximum contact pressure needed for forming a conformal interface with a surface topography of a given curvature. The indentation strain, e, is given by e¼k

rcontact rcurve

ð1Þ

where rcontact and rcurve are the contact radius and the topography radius, respectively (Fig. 1D), and k is a constant associated with indentation strain (33). Overall, the contact radius and indentation strain increase with increasing load until a conformal interface between the membrane and the hemisphere is achieved. The maximum contact pressure needed for achieving a conformal interface is determined science.org SCIENCE

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A

B

C

D

F

E

G

H

Fig. 1. Conceptual comparison of unstretchable and stretchable membranes. (A and B) Illustrations showing the wrapping of a piece of (A) unstretchable and (B) stretchable membrane around a pen. (C) Illustrations showing stretchable membranes with grid lines gradually conforming to a curved surface topography. (D) Diagram of a spherical indentation model and relevant parameters. (E and

by the Young’s modulus and the membrane thickness following the relationship "

 2 #1=3 p2 2 1 v21 1 v22 P0 þ þ 4 E1 E2   p2 1 v21 rcurve 3 P0 ¼1 8 E1 t3

ð2Þ

where P0 is the maximum contact pressure; E1 and v1 are the Young’s modulus and Poisson’s ratio of the membrane, respectively; t is the membrane thickness; and E2 and v2 are the Young’s modulus and Poisson’s ratio of the sphere, respectively (34, 35). The E/(1 − v2) is regarded as the plane-strain modulus, which is 130 kPa for human skin (36), 4 MPa for SCIENCE science.org

F) Contour maps showing the relationship between plane-strain modulus, film thickness, and (E) contact radius at a contact pressure of 1 kPa or (F) maximum contact pressure for a contact radius of 5 mm, highlighting that reducing thickness and plane-strain modulus favors a conformal interface. (G and H) Schematic diagram of (G) VDWTFs and (H) CVDTFs before and after stretching.

PDMS (37), and 2.8 GPa for polyimide (22). The difference in plane-strain modulus illustrates the large mechanical mismatch between human skin and the soft polymeric elastomer or typical plastics. Using Eqs. 1 and 2, we can calculate the maximum film thickness allowed to achieve a conformal interface with a topography of a given rcurve under a certain contact pressure for materials with a different plane-strain modulus (Fig. 1E). For example, to achieve a conformal interface with a skin topography of rcurve ~ 5 mm under a maximum contact pressure P0 of 1 kPa (the gentlest touch that a human can feel is 1 kPa) (38), the maximum allowed thickness is 0.3 mm for PDMS and 39 nm for polyimide. Similarly, we can also calculate the maximum contact pressure needed to form a conformal

interface with a given rcurve of 5 mm for materials with a different plane-strain modulus and thickness (Fig. 1F). These analyses highlight that the contact pressure needed to achieve a conformal interface is proportional to the Young’s modulus and thickness of the membrane and inversely proportional to the curvature of the radius of the surface topography. Although, in principle, the contact pressure on biological tissue can be minimized by reducing membrane thickness, the thickness cannot be reduced indefinitely for most polymeric materials owing to the limitation of the characteristic size of individual polymer chains and a precipitous decrease in mechanical properties below a critical thickness (e.g., 25 nm) (23). Conducting polymers that are suitable for electronic 25 FEBRUARY 2022 • VOL 375 ISSUE 6583

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applications usually show worse mechanical properties owing to their specific structural properties, such as chain length, regioregularity, and degree of polymerization. Adaptable and breathable VDWTFs

In our design of VDWTFs (Fig. 1G), the dangling bond–free nanosheets are staggered butted up against each other to establish broad-area plane-to-plane VDW contacts with minimum interfacial trapping states to ensure excellent charge transport across the intersheet grain boundaries. With the bond-free VDW interactions between the nanosheets, the VDWTFs offer a natural mechanical match to soft biological assemblies typically characterized by VDW interactions. When deformed, the bonding-free VDW interfaces allow nanosheets to slide or rotate against each other to accommodate the local tension or compression without breaking the broad-area VDW interfaces and conductive pathways (movie S1), which is essential for achieving unusual stretchability and structural stability in the ultrathin

Fig. 2. Material characteristics of VDWTFs and CVDTFs. (A) SEM and (B) TEM images showing VDWTFs assembled from staggered 2D nanosheets. (C and D) Photograph of the (C) VDWTFs and (D) CVDTFs floating on water. (E) Stress–strain curve of a freestanding VDWTF. Tensile loads cause 2D nanosheets in VDWTFs to slide or rotate against each other, resulting in unusual stretchability. (F) Photographs of the VDWTF at different tensile strains. (G) Resistance–strain curve of the VDWTF and CVDTF on a PDMS substrate. (H to K) SEM images showing the contact interface between the 4.3-mm-diameter silica microspheres of different configurations with [(H) and (I)] VDWTFs or [(J) and (K)] CVDTFs. Scale bars, 2 mm. (L) Water contact angles of a VDWTF (top) and a CVDTF (bottom). (M) Optical micrographs of a VDWTF suspended over a polyimide substrate with circular holes, confirming structural robustness of the freestanding VDWTFs. (N) Water vapor transmission through VDWTFs of different thickness versus transepidermal water loss (TEWL). See the supplementary materials for a description of the “open bottle” and “closed bottle” conditions.

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freestanding format. The mechanical deformation of VDWTFs is readily transformed into intersheet sliding or rotation to accommodate local strains and deformations and overcome topological limitations, thus endowing exceptional malleability and adaptability to irregular and dynamically changing surface topographies. Lastly, the VDWTFs feature a percolating network of nanochannels (dictated by nanosheet thickness: ~3 nm) winding around the staggered nanosheets for gas and/or nutrient permeation, which is critical for the breathability of bioelectronics (movie S2). This combination of electronic and mechanical properties originates from the VDW interactions among the staggered 2D nanosheets and is difficult to achieve in typical chemical vapor deposition–grown thin films (CVDTFs) (Fig. 1H). The electrical and mechanical properties of CVDTFs—with their typical polycrystalline structure consisting of laterally stitched domains—are strongly influenced by the grain size, grain orientation, shape, and density of grain boundary defects. The stiff and strong

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covalent bonding within the grains and disordered bonds at the grain boundaries of the CVDTFs (marked with red arrows in Fig. 1H) can result in the formation of cracks and ruptures that propagate along the grain boundaries when they are deformed, thereby causing mechanical fragmentation and electronic disintegration under minimal strain (movie S1). Structural and mechanical properties of VDWTFs

Molybdenum disulfide (MoS2) nanosheet ink was prepared using an intercalation-exfoliation process and assembled into VDWTFs using a spin coating process (see supplementary materials). Scanning electron microscopy (SEM) and transmission electron microscopy (TEM) studies show a staggered nanosheet thin film (Fig. 2, A and B) with an overall film thickness of ~10 nm (fig. S1A). The MoS2 nanosheets, with a thickness of ~3 nm and lateral dimensions ranging from less than one to several micrometers, are staggered butted up against each

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other to form broad-area plane-to-plane VDW interfaces with an average of ~3 to 4 nanosheets staggered in a crisscross manner in the vertical direction. The broad-area bond-free VDW interfaces allow adjacent nanosheets to slide or rotate against each other to accommodate local structural perturbation and reduce the strain-induced cracks and fractures, thus ensuring structural integrity even in the freestanding format. For example, the continuous freestanding VDWTFs can be readily floated on water (Fig. 2C and movie S3), completely folded repeatedly without tearing (movie S4), and suspended over open holes without rupturing (Fig. 2M). In comparison, the freestanding polycrystalline CVDTFs (fig. S1B) easily fragment on water (Fig. 2D and movie S3) and are too fragile to suspend over open holes (fig. S2). The stress–strain curve of the freestanding VDWTFs shows a well-behaved linear relationship up to a tensile strain of 43% (Fig. 2E), with a Young’s modulus (~47.3 MPa) about three orders of magnitude smaller than that of bulk MoS2 (~200 GPa). The greatly reduced modulus indicates that the film deformation is transformed into interlayer sliding or rotation among nanosheets rather than an intrinsic lattice expansion (Fig. 2F). Beyond the linear regime, the stress shows little increase with further increasing of the tensile strain to ~62%, indicating that interlayer sliding or rotation gradually reaches the limit and begins to initiate local rupture, which further aggravates at higher tensile strain and leads to complete rupture at a tensile strain of >120%. We compared the electronic properties of the VDWTFs and CVDTFs as a function of the applied strain (Fig. 2G). Because CVDTFs cannot maintain macroscopic structural integrity in the freestanding form, the measurement was done on films supported on PDMS substrates to ensure a robust comparison. For CVDTFs, the relative resistance exhibits a gradual linear increase at a tensile strain of 55%, with a stable recoverable resistance under repeated strain cycles (fig. S3). When the tensile strain is >55%, the resistance increases sharply, indicating the formation of microscopic cracks and substantially reduced conductive pathways. Adaptability, wettability, and permeability of VDWTFs

We evaluated the adaptability and conformability of the VDWTFs to microscopic surface topographies. SEM studies revealed that the VDWTFs exhibit highly conformal interfaces with not only the microsphere SCIENCE science.org

(4.3-mm-diameter) arrays (Fig. 2H) but also the isolated single microspheres, two- or threemicrosphere clusters (Fig. 2I), conformally wrapping around the microspheres without tearing. By comparison, the CVDTFs on the same surface topography are much less conformal and show abundant microcracks (Fig. 2, J and K), particularly at the high strain or stress concentration region (e.g., the foot of the microspheres or the space between two adjacent microspheres). Surface wettability is essential for ensuring proper adhesion between electronic membranes and living organisms (Fig. 2L). With abundant edge structures in individual nanosheet building blocks, the VDWTFs exhibit better wettability (with a water contact angle of 40.2°) than CVDTFs (water contact angle of 76.3°), which is desirable for intimately interfacing with wet biological tissues. Lastly, membrane permeability or breathability is required for gas or nutrient exchange with the environment in bioelectronic applications. Water vapor transmission studies (see supplementary materials) reveal water vapor transmission rates of 34 and 26 mg cm−2 hour−1 for the 10-nm-thick and 30-nm-thick freestanding VDWTFs, respectively, suspended over an open hole (Fig. 2, M and N), about six to eight times higher than the typical transepidermal water loss (TEWL) rate (4.4 mg cm−2 hour−1) (39). Such permeability of the continuous VDWTFs is attributed to the staggered nanosheet structures, with a highly interconnected network of nanochannels (with the channel thickness dictated by the nanosheet thickness: ~3 nm) winding around the staggered nanosheets (movie S2). Leaf-gate VDWTF transistors

Given their exceptional stretchability, conformability, and breathability, the VDWTFs can directly merge with living organisms to form seamless electronic-bio hybrids. Whereas previous attempts sought to augment plant function with electroactive materials or to simply use the plant as an unconventional supporting substrate, our approach was to transfer the VDWTFs onto a leaf to form a leaf-gate transistor, in which the plant leaf functions as a modulating gate and constitutes an active part of the device. We chose the Senecio mandraliscae leaf (Fig. 3A), which contains abundant electrolyte in mesophyll, as a model system to study the leaf-gate transistors. For the leaf-gate transistor operations (Fig. 3B), the VDWTF channel is contacted with serpentine-mesh Au electrodes (Fig. 3C, top) to prevent breaking of the Au thin-film electrodes by local strain on the rough leaf surface, while an inserted tungsten probe establishes electrical contact to the electrolyte within the leaf to form the gate electrode. The transferred VDWTFs form a highly conformal interface with

complete compliance, as confirmed by the optical microscopy (Fig. 3D) and SEM studies (Fig. 3E). The function of the leaf-gate transistor relies on the ionic gating effect (in the electrolyte of the leaf gate) to modulate the electronic properties of the VDWTFs, for which the microscopically conformal interface is essential for efficient gating. The leaf-gate transistor shows a typical n-channel transfer curve with an on/off ratio of ~100 (Fig. 3, F to H). The relatively low on/off ratio is limited by the direct leakage into the transistor channel from the leaf gate through direct resistive coupling. With a highly conformal interface and efficient gate coupling, the leaf-gate transistor can operate at a low operating voltage amenable to biological systems. Skin-gate VDWTF transistors

VDWTFs can be transferred onto human skin with a highly conformal interface to form skingate transistors (fig. S4). In the skin, electrolytes help conduct electricity, regulate pH levels, and keep the body’s hydration system in check. The conformal integration of VDWTFs with the skin textures (fig. S5, A to C) results in skin-gate transistors in which the electrolyte in human skin effectively modulates the conduction in VDWTFs (Fig. 4, A and B). Proper skin-gate transistor function requires a conformal interface with an intimate interaction between the VDWTF channel and the epidermis, in which the epidermis can be modeled by a parallel circuit consisting of a capacitor and a resistor, and the dermis and underlying subcutaneous tissues modeled by a resistor (Fig. 4B). We investigated the conformability of the freestanding VDWTFs on a forearm skin replica made of Ecoflex silicone rubber and compared it with the same VDWTF supported on a 1.6-mm-thick PI substrate (Fig. 4C). The freestanding VDWTF adapts to the skin textures and makes an excellent conformal interface without apparent cracking or tearing. In contrast, the 1.6-mm-thick PI substrate and the VDWTF with the PI substrate show much less conformal contact, with most of the fine skin textures, such as the surface wrinkles and pits, hidden (Fig. 4C, right side). A profilometry height profile analysis shows that surface topography of the skin replica covered with the freestanding VDWTF is essentially the same as that without the VDWTF (Fig. 4, D and E), suggesting a fully conformal interface. In contrast, for the area covered with the VDWTF supported by the 1.6-mm-thick PI substrate (Fig. 4, F and G), the surface topography is largely flattened, suggesting that the 1.6-mm-thick PI substrate is already too thick to naturally adapt to the skin textures to form microscopically conformal interfaces. 25 FEBRUARY 2022 • VOL 375 ISSUE 6583

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The ability of a membrane to make a conformal interface with the surface topography can be determined by bending stiffness (22). The effective bending stiffness (EI) for a multilayer membrane can be described as ( ! " N i X X Ei 1 2 h þ hi hj EI ¼ 3 i 1 v2i i¼1 j¼1 #2 hneutral

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ð4Þ where hneutral denotes the neutral mechanical plane; i represents the ith layer of the film; hi, Ei, and vi represent the thickness, the elastic modulus, and Poisson’s ratio, respectively; and N is the number of layers (40). Notably, with its ultrasmall thickness and low elastic modulus, the freestanding 10-nm-thick VDWTF exhibits a bending stiffness of 4.2 × 10−9 GPa·mm3, which is about eight orders of magnitude smaller than that of the 1.6-mmthick VDWTF/PI film (0.97 GPa·mm3). 856

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The VDWTFs transferred onto human skin show excellent natural adaptability to changing skin textures and retain conformal contact without apparent fracturing or flaking throughout stretching, squeezing, and relaxing cycles (Fig. 4H), highlighting the highly adaptable nature of the VDWTFs to dynamically evolving biological substrates. In contrast, the CVDTFs transferred onto human skin easily fracture and flake off when the skin is subjected to similar deformation. Figure 4I shows the remaining area of both films on the skin replica versus the number of squeezing-and-stretching cycles. Because the freestanding CVDTFs are not strong enough for processing and transferring, they are transferred onto the skin replica with methyl methacrylate (MMA) support. After the transfer process, the CVDTFs quickly flake off once the MMA is dissolved away with acetone vapor. The remaining area instantly decreases to ~50% of the original area and, after 100 stretching cycles, further decreases to 40% of the original area, with mostly fractured domains. The fracturing and flaking are attributed to the unstable membrane–skin interface, which is associated with their limited stretchability, conformability, and poor wettability. In contrast, the VDWTFs show superior stretchability and conformability to the dynamically changing skin replica with no apparent fracturing or flaking, retaining essentially

Fig. 3. Leaf-gate VDWTF transistors. (A) Diagram of a Senecio mandraliscae leaf. (B) Cross-sectional view of the leaf-gate transistor with Au source and drain electrodes (“S” and “D,” respectively) and an inserted tungsten gate electrode (“G”). (C) Schematic illustration (top; leaf, light green; VDWTF, dark green; Au electrodes, yellow; tungsten probe, black dot) and photograph of the leaf-gate transistor (bottom). (D) Optical image of a VDWTF with serpentine Au electrodes transferred onto the plant leaf. (E) Colorized SEM image of the VDWTF on the leaf. (F) Output characteristics of a leaf-gate transistor. Vds, drainsource voltage; Ids, drain-source current. (G and H) Transfer curves with (G) linear and (H) logarithmic axis. Vg, gate voltage.

100% surface coverage after the repeated squeezing-and-stretching cycles. The output and transfer curves of the skingate VDWTF transistor demonstrate expected transistor functions (Fig. 4, J and K) with a low operating voltage suitable for biological systems. Furthermore, the skin-gate VDWTF transistor can maintain stable operation while undergoing various mechanical deformations (Fig. 4L), establishing a foundation for applications in probing and amplifying electrophysiological signals. Monitoring electrophysiological signals with skin-gate VDWTF transistors

Given that many biopotential signals show transient responses, we have evaluated the frequency response of the skin-gate transistors. The response times, t, of the skin-gate transistors are probed by measuring the current response under a 20-ms pulse of 100-mV gate voltage (Fig. 5A). A response time of 7 ms is achieved by fitting experimental data with an exponential function (Fig. 5B). Furthermore, the skin-gate transistors show a cut-off frequency (at which the transconductance drops by 3 dB from its plateau value) of ~100 kHz (Fig. 5C), which is sufficient for monitoring most electrophysiological signals from the human body. We explored the skin-gate VDWTF transistors for monitoring electrocardiography (ECG). science.org SCIENCE

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Fig. 4. Skin-gate VDWTF transistors. (A) The structure of human skin. (B) Schematic of a skin-gate VDWTF transistor with Au source and drain electrodes and an iron rod gate electrode held by a human subject. (C) Photograph of the freestanding VDWTF on a replica of human skin (left) and the VDWTF supported by a 1.6-mm-thick polyimide substrate on a replica of human skin (right). (D to G) Height profiles corresponding to the line scan in different areas of (C). (H) Skingate VDWTF transistor on human skin under different types of mechanical deformation. (I) Remaining area of VDWTFs and CVDTFs on skin replicas as a function of stretching cycles (10% tensile strain). Scale bars, 2 mm. (J) Output and (K) transfer curves of a skin-gate VDWTF transistor. (L) Transfer curves under different types of deformation.

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In this measurement, the VDWTF pad is placed on the left forearm and the gate electrode is adhered on the symmetrical position (right forearm) (Fig. 5D), and each VDWTF pad works with an Ag/AgCl electrode nearby for comparison. Among the common challenges in measuring ECG with conventional Ag/AgCl electrodes are the motion artifacts due to sliding, inconsistent adhesion, and a mechanical mismatch at the electrode–skin interface induced by skin deformation, leading to a greatly reduced signal-to-noise ratio (SNR), from 44.3 dB before motion (Fig. 5E) down to 28.5 dB during motion (Fig. 5, F and G). With the conformal skin-gate transistors, motion artifacts are mitigated, achieving an essentially comparable SNR of 49.8 dB before human motion (Fig. 5E and fig. S6) and 49.2 dB

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during human motion (Fig. 5, F and G). With reduced motion artifacts, the ECG signals recorded by the skin-gate transistors (red line) show clear P, QRS, and T waves, with no abnormal deviations and relatively stable baseline during human motion (Fig. 5, F and G). In contrast, such fine signals are less resolvable by the Ag/AgCl electrodes (Fig. 5G). High-fidelity, real-time electroencephalogram (EEG) recording is important for monitoring cerebral activities, studying cognitive behaviors, and developing insights into various neurological disorders. Cerebral activities can be divided into five frequency bands: delta wave (0 to 4 Hz), theta wave (4 to 8 Hz), alpha wave (8 to 12 Hz), beta wave (12 to 30 Hz), and gamma wave (>30 Hz), with each frequency band associated with different mental states. To test

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the ability to acquire high-quality neurophysiological signals, we placed the VDWTF transistor over the left side of the forehead (Fp1) according to the international 10-20 system of EEG electrode placement (17) and recorded voltage differences relative to a reference electrode placed over the left occipital region (O1) (Fig. 5H). When the human subject is relaxed with eyes closed, the EEG background is usually characterized by the posteriorly dominant alpha rhythm (posterior dominant rhythm) with a prominent 8- to 12-Hz (alpha) oscillation (Fig. 5, I and J), corresponding to brain activities such as meditation and mindfulness that can reduce stress levels. The alpha rhythm typically attenuates considerably upon eye opening, as clearly seen in the spectrogram of the EEG 25 FEBRUARY 2022 • VOL 375 ISSUE 6583

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Fig. 5. Skin-gate VDWTF transistors for monitoring transient skin potentials. (A) Relative drain current (DIds) of a skin-gate VDWTF transistor stimulated by 5 kHz 0.1-V 20-ms-wide gate pulses at a Vds of 0.1 V. (B) The response time of the skin-gate VDWTF transistor to a square gate pulse (blue dashed line). (C) Normalized transconductance at various frequencies. (D) Schematic diagram of the ECG measurement with a Vds of 0.5 V and a Vg of 0.5 V. (E and F) The ECG signals measured by the skin-gate transistor (red line) and Ag/AgCl electrode (black line) (E) before and (F) during human exercise. a.u., arbitrary units. (G) Zoomed-in view of boxed portion

signal measured by the skin-gate transistor (Fig. 5K), showing the dynamic activity of the alpha rhythm coupled with cyclic eye closing and opening. Conclusions

Here, we report on mechanically robust freestanding VDWTFs assembled from 2D nanosheets for highly stretchable, adaptable, conformal, and breathable membrane electronics. The bond-free VDW interfaces among the nanosheets enable sliding and rotating degrees of freedom to render extraordinary mechanical flexibility, stretchability, and malleability. The staggered nanosheet architecture also features a percolation network of nanochannels for excellent permeability or breathability. The ultrathin freestanding VDWTFs are structurally robust with an excellent mechanical match to soft biological tissues, naturally adapting to microscopic topographies 858

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in (F), showing clear P, QRS, and T waves from the skin-gate transistor but only a QRS wave and motion artifacts from the Ag/AgCl electrodes. (H) Schematic diagram of the EEG measurement. (I) Recorded EEG signals using a skin-gate transistor when a human subject was engaged in two mental states (closed eyes and open eyes). Eye blink artifacts are also visible. (J) Fast Fourier transform (FFT)–processed frequency distributions of the EEG signals in (I). (K) Time-frequency spectrograms of the EEG signals recorded during cyclic eye closing and opening, showing dynamic activity of the alpha rhythm at ~10 Hz.

and directly integrating with living organisms through highly conformal interfaces, endowing living organisms with electronic functions. The VDWTFs can thus function as versatile electronic membranes that actively adapt to the environment while retaining sufficient electronic performance for sensing, signal amplification, processing, and communication.

RE FERENCES AND NOTES

1. G. D. Spyropoulos, J. N. Gelinas, D. Khodagholy, Sci. Adv. 5, eaau7378 (2019). 2. I. You et al., Science 370, 961–965 (2020). 3. F. Ershad et al., Nat. Commun. 11, 3823 (2020). 4. Q. Li et al., Nano Lett. 19, 5781–5789 (2019). 5. S. Wang et al., Nature 555, 83–88 (2018). 6. K. Sim et al., Sci. Adv. 5, eaav5749 (2019). 7. E. Stavrinidou et al., Sci. Adv. 1, e1501136 (2015). 8. K. Kwon et al., Nat. Electron. 4, 302–312 (2021). 9. J. Koo et al., Nat. Med. 24, 1830–1836 (2018). 10. M. Han et al., Nat. Biomed. Eng. 4, 997–1009 (2020). 11. M. Bariya, H. Y. Y. Nyein, A. Javey, Nat. Electron. 1, 160–171 (2018).

12. J. A. Rogers, R. Ghaffari, D.-H. Kim, Eds., Stretchable Bioelectronics for Medical Devices and Systems (Springer, 2016). 13. S. H. Chae et al., Nat. Mater. 12, 403–409 (2013). 14. J. Yoon et al., Nat. Mater. 7, 907–915 (2008). 15. D.-Y. Khang, H. Jiang, Y. Huang, J. A. Rogers, Science 311, 208–212 (2006). 16. D.-H. Kim et al., Science 333, 838–843 (2011). 17. L. Tian et al., Nat. Biomed. Eng. 3, 194–205 (2019). 18. Z. Huang et al., Nat. Electron. 1, 473–480 (2018). 19. J. Rivnay et al., Nat. Rev. Mater. 3, 17086 (2018). 20. Y. Fang, X. Li, Y. Fang, J. Mater. Chem. C 3, 6424–6430 (2015). 21. L. Cai et al., Nat. Commun. 8, 496 (2017). 22. Z. Yan et al., Adv. Sci. 4, 1700251 (2017). 23. Y. Liu et al., Macromolecules 48, 6534–6540 (2015). 24. J. N. Coleman et al., Science 331, 568–571 (2011). 25. Z. Lin et al., Nature 562, 254–258 (2018). 26. Z. Lin, Y. Huang, X. Duan, Nat. Electron. 2, 378–388 (2019). 27. D. McManus et al., Nat. Nanotechnol. 12, 343–350 (2017). 28. J. W. Jeong et al., Adv. Mater. 25, 6839–6846 (2013). 29. J. A. Rogers, T. Someya, Y. Huang, Science 327, 1603–1607 (2010). 30. Y.-K. Lee et al., Sci. Adv. 6, eaax6212 (2020). 31. C. E. Carraher Jr., Giant Molecules: Essential Materials for Everyday Living and Problem Solving (Wiley, ed. 2, 2003). 32. Y.-Q. Zheng et al., Science 373, 88–94 (2021). 33. B. Xu, X. Chen, J. Mater. Res. 25, 2297–2307 (2010). 34. O. Scott, M. Begley, U. Komaragiri, T. Mackin, Acta Mater. 52, 4877–4885 (2004).

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35. X. Fang, C. Zhang, X. Chen, Y. Wang, Y. Tan, Acta Mech. 226, 1657–1672 (2015). 36. S. Wang et al., J. Appl. Mech. 79, 031022 (2012). 37. Y. Yu, D. Sanchez, N. Lu, J. Mater. Res. 30, 2702–2712 (2015). 38. J. J. Boland, Nat. Mater. 9, 790–792 (2010). 39. J. Kottner, A. Lichterfeld, U. Blume-Peytavi, Arch. Dermatol. Res. 305, 315–323 (2013). 40. T. Pan et al., Adv. Funct. Mater. 27, 1702589 (2017). ACKN OW LEDG MEN TS

We acknowledge the Electron Imaging Center at UCLA for STEM and TEM technical support, as well as the Nanoelectronics Research Facility at UCLA for device fabrication technical support. We thank M. Liu for chemical vapor deposition thin-film samples and Sphere Studio for assistance with animations in movies S1 and S2. Funding: X.D.

REPORTS

acknowledges the UCLA Physical Sciences Entrepreneurship and Innovation Fund and partial support from CNSI Noble Family Innovation Fund. Author contributions: X.D. and Y.H. conceived of the research. X.D. and Z.Y. designed all experiments. Z.Y. fabricated the electronic devices and analyzed the results. Z.Y., Z.L., D.X., and F.S. fabricated the solutionprocessable VDWTFs. D.X. and P.W. assisted with the electronic device fabrication. Z.Y. and P.W. performed the electronic measurements. Z.Y., J.Z., and D.X. conducted the mechanical measurements. Z.Y., B.C., Z.L., and C.W. performed the electron microscopy analyses on VDWTFs. Z.Y. and D.X. conducted the test of water vapor transmission rate for VDWTFs. Z.Y. and H.R. took optical images for organism-gated electronic devices. Z.Y., D.X., P.W., X.Z., and J.C. conducted and participated in the on-body measurements. L.W., H.R., and P.W. assisted with e-beam evaporation. X.D. and Z.Y. co-wrote the paper. X.D. and Y.H. supervised the research. All authors discussed the results and commented on the manuscript. Competing interests: A

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IMMUNOLOGY

Trained ILC3 responses promote intestinal defense Nicolas Serafini1, Angélique Jarade1, Laura Surace1, Pedro Goncalves1, Odile Sismeiro2, Hugo Varet2,3, Rachel Legendre2,3, Jean-Yves Coppee2, Olivier Disson4, Scott K. Durum5, Gad Frankel6, James P. Di Santo1* Group 3 innate lymphoid cells (ILC3s) are innate immune effectors that contribute to host defense. Whether ILC3 functions are stably modified after pathogen encounter is unknown. Here, we assess the impact of a time-restricted enterobacterial challenge to long-term ILC3 activation in mice. We found that intestinal ILC3s persist for months in an activated state after exposure to Citrobacter rodentium. Upon rechallenge, these “trained” ILC3s proliferate, display enhanced interleukin-22 (IL-22) responses, and have a superior capacity to control infection compared with naïve ILC3s. Metabolic changes occur in C. rodentium–exposed ILC3s, but only trained ILC3s have an enhanced proliferative capacity that contributes to increased IL-22 production. Accordingly, a limited encounter with a pathogen can promote durable phenotypic and functional changes in intestinal ILC3s that contribute to long-term mucosal defense.

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pecialized immune cells promote barrier function and maintain microbial tolerance at mucosal surfaces (1); these include effector and memory T cells that provide long-term immune-surveillance and recall responses as well as diverse innate lymphoid cells (ILCs) (2, 3). Group 3 ILCs (ILC3s) are highly enriched in the gut where they orchestrate lymphoid tissue development and mucosal defense (3, 4). Largely devoid of pattern recognition receptors (5), ILC3s are indirectly activated after infection by soluble factors [interleukin-1b (IL-1b) and IL-23] derived from epithelial and hematopoietic sentinel cells (4) and, in turn, secrete IL-17 and

1

Institut Pasteur, Université de Paris, Inserm U1223, Innate Immunity Unit, Paris, France. 2Institut Pasteur, Université de Paris, Transcriptome and Epigenome Platform–Biomics Pole, Paris, France. 3Institut Pasteur, Université de Paris, Bioinformatics and Biostatistics Hub, Paris, France. 4Institut Pasteur, Université de Paris, Inserm U1117, Biology of Infection Unit, Paris, France. 5Laboratory of Cancer and Immunometabolism, Center for Cancer Research, National Cancer Institute, National Institutes of Health, Frederick, MD, USA. 6MRC Centre for Molecular Bacteriology and Infection, Department of Life Sciences, Imperial College London, London, UK.

*Corresponding author: Email: [email protected]

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IL-22 to protect the host (6–9). ILC3s are active during fetal lymphoid tissue organogenesis (10, 11), and initial encounters with microbial flora in early postnatal life modifies ILC3 subset distribution and cytokine production (6, 12). Whether ILC3s exhibit any degree of long-term adaptation to a commensal or pathogen encounter that results in heightened immunological function remains to be demonstrated. To study whether persistent functional changes occur in intestinal ILC3s after microbial encounter, we used Citrobacter rodentium, a mouse pathogen that provokes an enterocolitis with disease similarities to human enteropathogenic Escherichia coli infection (13). C. rodentium attaches and effaces the distal small intestine and colon, provoking innate dendritic cell (DC)–induced ILC3 activation as well as generation of adaptive antigen-specific B and T cells (6, 9, 14). To focus on intestinal ILC3 responses to C. rodentium that are independent of adaptive immune priming (14) and infection-associated dysbiosis (13, 15), we limited the infection window using antibiotics (Abx) (15) (fig. S1, A to E). Indeed, a short course of ciprofloxacin was sufficient to re-

provisional patent application (no. 63/308,028) has been filed on the stretchable van der Waals thin films. The authors declare no other competing interests. Data and materials availability: All data are available in the manuscript or the supplementary materials. SUPPLEMENTARY MATERIALS

science.org/doi/10.1126/science.abl8941 Materials and Methods Supplementary Text Figs. S1 to S7 References Movies S1 to S4 12 August 2021; accepted 20 January 2022 10.1126/science.abl8941

strict adaptive T helper type 22 (TH22) responses, whereas innate ILC3-dependent IL-22 responses were activated normally (fig. S1, F to H). Although Abx treatment alone transiently modified intestinal bacterial communities (fig. S2, A to C), no long-term impact on ILC3 function (fig. S2, D to F) or on microbial diversity (fig. S3) was observed. We characterized innate ILC3 and adaptive TH22 immune responses in this modified C. rodentium infection model using RorcGFP and Il22TdT reporter mice (16, 17) (Fig. 1, A and B; and fig. S4) (GFP, green fluorescent protein; TdT, tdTomato). T cell and ILC3 populations were generally stable during the initial infection, but C. rodentium reinfection 1 month after Abx treatment resulted in a rapid increase in intestinal NKp46+ and CCR6+ ILC3 subsets with little effect on T cells (Fig. 1, B and C). Absolute numbers and frequencies of IL-22–expressing ILC3s increased in a similar fashion, whereas IL-22–expressing T cells were largely unchanged (Fig. 1, D to F; and fig. S5). C. rodentium challenge and rechallenge experiments in mice not treated with ciprofloxacin showed similar ILC3 responses, indicating the innocuous effects of the Abx treatment (fig. S6, A to C). CD4+ T cell numbers and frequencies of IL-17A–, IL-22–, and interferon-g (IFN-g)–producing T cells were not affected (fig. S6, B to E). Thus, the homeostasis and function of intestinal IL-22– producing ILC3s can be selectively modified after an Abx-controlled subclinical C. rodentium infection. Mucosal IL-22 production activates epithelial responses during pathogen infection and is required for resistance to C. rodentium (18, 19). Bacterial growth after first infection (denoted “CR”) was not observed after reinfection of Abx-cleared infected mice (denoted CR-AbxCR or “CRACR”) (Fig. 1, G and H), suggesting that enhanced ILC3 function in CRACR mice might play a role in the resistance to bacterial rechallenge. DC activation was noted during rechallenge, whereas monocytes, macrophages, and granulocytes were largely unchanged (fig. S7). Taken together, a limited initial exposure of intestinal ILC3s to pathogenic bacteria can 25 FEBRUARY 2022 • VOL 375 ISSUE 6583

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140 120 100 80 60 40 20 0

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Il22TdT+ cells (% of CD45.2+)

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generate a highly functional and persistent ILC3 subset, which we refer to hereafter as “trained ILC3s” (Tr-ILC3s). Enhanced Tr-ILC3 responses persisted 4 months after C. rodentium reinfection of Abx-cleared mice (Fig. 2A), with reduced bacterial loads upon reinfection (Fig. 2B). Absolute numbers of total ILC3s (Fig. 2C) and IL-22+ ILC3s (Fig. 2, D and E) were significantly increased in CRACR mice that were reinfected 4 months later with diverse ILC3 subsets as dominant IL-22 producers (Fig. 2, F and G). Because the DNA-binding protein inhibitor ID2 is highly expressed in differentiated ILCs (20, 21), we used Id2-regulated inducible fate25 FEBRUARY 2022 • VOL 375 ISSUE 6583

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Fig. 1. Tr-ILC3s efficiently control pathogenic bacteria rechallenge. (A) The experimental design for (B) to (H) is shown at the top. RorcGFPIl22TdT mice received ciprofloxacin (Abx; 100 mg kg–1 day–1) after C. rodentium infection (CR). One month later, the mice were reinfected with C. rodentium (CRACR). A representative steady-state immunofluorescence analysis of RORgt+ (green) and Il22TdT+ (magenta) cells in the small intestine is shown at the bottom. Nuclei were stained with 4′,6-diamidino-2-phenylindole (DAPI) (blue) (scale bar, 20 mm). SILP, small intestine lamina propria; D0, day 0. (B) Intestinal NKp46+ and CCR6+ ILC3s were analyzed by flow cytometry (top). Absolute numbers of ILC3s and T cells in the small intestine lamina propria (n = 4 to 12 for each time point) are shown at the bottom. (C) Absolute numbers of intestinal NKp46+ (top) and CCR6+ (bottom) ILC3s determined with representative data from three independent analyses (n = 3 to 7 for each time point). (D) Small intestinal Il22TdT+ ILC3 (CD45+CD3−RorcGFP+) and T cell (CD45+CD3+) frequencies at day 0 (top). Absolute numbers of Il22TdT+

860

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cells were determined with representative data from six independent analyses (n = 4 to 12 for each time point) (bottom). (E) Absolute numbers of IL-22+ (protein) cells were analyzed after ex vivo IL-23 (top) and IL-1b (bottom) stimulation (n = 4 to 9 for each time point). (F) Il22TdT expression in ILC1s (CD3−NKp46+NK1.1+), NKp46+ ILC3s, and CCR6+ ILC3s (left). Representative data are from three independent analyses. The frequencies of Il22TdT+NKp46+ and NKp46− ILC3 subsets in the small intestine lamina propria after reinfection are shown on the right (CRACR; n = 3 to 7 for each time point). (G) C. rodentium growth monitored by IVIS imaging (CR, n = 12; CRACR, n = 12). Representative pseudocolor images are shown (color scale in photons s–1 cm–2 sr–1). (H) Fecal C. rodentium counts (CR, n = 8; CRACR, n = 13). Data are representative of three independent experiments. Each graph corresponds to the mean ± SEM of the values obtained. n.d. indicates not detected and ***P < 0.001 using two-tailed Mann-Whitney test.

mapping (22) to track ILCs under steady state and after infection (Fig. 2H). All ILCs were red fluorescent protein (RFP)–labeled, with a somewhat higher percentage of RFP+ ILC3s after C. rodentium infection (CR and CRA conditions; Fig. 2I). By contrast, most RFP+ ILC1s and ILC2s were lost in CRACR mice, whereas labeled RFP+ ILC3 subsets were maintained (Fig. 2I). These results indicate that diverse Tr-ILC3s can persist after a limited exposure to C. rodentium and may preferentially expand after pathogen reencounter. We determined if Tr-ILC3s could be generated in the absence of adaptive immunity (Fig. 3A). Absolute numbers of IL-22+ ILC3s were significantly increased in CRACR Rag2−/−

mice (Fig. 3B), which had reduced bacterial loads compared with the CR-infected Rag2−/− mice (Fig. 3C). IL-22 production was required for Tr-ILC3–mediated protection against C. rodentium (Fig. 3A) because Rag2−/−Il22−/− CRACR mice did not survive reinfection (Fig. 3, D and E). We next compared the protective capacity of adoptively transferred naïve versus Tr-ILC3s in vivo (Fig. 3F). CR-infected Il22−/− mice that received naïve ILC3s exhibited body weight loss and succumbed about 2 weeks after infection (Fig. 3G). By contrast, CRinfected Il22−/− mice that received Tr-ILC3s recovered and survived (Fig. 3G). Thus, the enhanced functional capacity of Tr-ILC3s science.org SCIENCE

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Id2 (RFP )

Id2 RFP+ cells (% of ILC)

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Il22TdT+ ILC3 ( 104)

ILC3 ( 104)

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Il22TdT+ ILC3 ( 104)

Fig. 2. Tr-ILC3s show long-term C 150 B 109 D 130 A RorcGFP Il22TdT * 108 * persistence. (A) Experimental 100 125 GFP TdT Ncr1 Il22 ** 107 60 design for (B) to (H). 106 100 105 ns 40 75 ns RorcGFP×Il22TdT and Ncr1GFP×Il22TdT 104 ** ** 103 50 mice received ciprofloxacin 20 CR Abx CR 102 25 1 –1 –1 10 (Abx; 100 mg kg day ) after 0 0 100 - + + + + + CR - + + + + + CR D0 D3 D120 CR CRACR C. rodentium infection. Four months - - - + - + CRACR - - - + - + CRACR later, the mice were reinfected 1 4 Time (mo) Time (mo) CRACR 1 4 CR with C. rodentium (CRACR). CRACR CRACR E F G ILC3 - after reinfection (D3) + + (B) Fecal C. rodentium counts 4 months 4 months ILC3 - after reinfection (D3) ns 4 months after primo infection 4 months after primo infection (CR, n = 8; CRACR, n = 12). CFU, 6 12 25 ** ** 7.4 38.1 28.1 colony forming units. (C and 5 10 20 18 D) Absolute numbers of total (C) 4 8 15 * 3 6 ns (n = 3 to 8) and Il22TdT+ (D) ns 10 ns 2 4 (n = 3 to 9) ILC3s in the small 5 1 2 38 41 intestine lamina propria. (E) Abso0 0 0 + + + NKp46 CCR6 DN CR CRACR lute numbers of intestinal IL-22 NKp46+ CCR6+ DN NKp46+ CCR6+ DN CCR6 ILC3s (protein; n = 3 to 5) after Id2CreERT2+ ex vivo IL-23 and IL-1b stimulation ILC1 H Rosa26 I RFP ILC2 CR (D3) CRA (D30) CRACR (D33) Tmx CR Analysis CRACR (D33) 3 days after infection or reinfection. ILC3 60 5.5 4.4 46.5 25.4 27.9 45.5 35.6 40.9 57.1 51.9 (F and G) Frequency and absolute 36.2 50.9 50 -D4 D0 D3 numbers of ILC3s (F) and Il22TdT+ ILC3 40 CR Abx CR 30 (G) subsets in CRACR mice were 20 Tmx determined (n = 3 to 5). DN, double D0 D4 D8 D30 10 negative. (H) Fate-mapping Analysis Tmx 0 RFP+ ID2+ ILC1 ILC2 ILC3 ILC1 ILC2 ILC3 ILC1 ILC2 ILC3 NKp46+ DN CCR6+ CR CRA CRACR protocol. Id2CreERT2+×Rosa26RFP mice received ciprofloxacin (Abx; 100 mg kg–1 day–1) 3 days after C. rodentium infection. Mice received tamoxifen (Tmx) by intraperitoneal injection and were analyzed as shown. (I) Analysis of Id2RFP+ cells in ILC1 (CD3−NKp46+NK1.1+), ILC2 (CD3−CD127+CD90.2+KLRG1+), and ILC3 subsets (left) for the protocol shown in (H). Percentages of Id2RFP+ cells of the total ILCs in CR, CRA, and CRACR mice were determined (n = 3 to 5) (right). Each graph corresponds to the mean ± SEM of the values obtained. ns indicates not significant, *P < 0.05, and **P < 0.01 using two-tailed Mann-Whitney test.

5

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ILC3 ( 104)

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–/– Rag2 –/– Fig. 3. Tr-ILC3s show A B 300 C 109 * Rag2 150 enhanced IL-22Ðmediated 8 10 125 250 Rag2 / ** protection. (A) ExperimenRag2 / Il22 / 107 100 200 tal design for (B) to (E). 6 10 75 150 Rag2−/− and Rag2−/−Il22−/− CR Abx CR 105 50 100 mice received ciprofloxacin 104 25 50 D40 (Abx; 100 mg kg–1 day–1) D0 D3 D30 103 0 0 CR CRACR - + + + CR - + + + CR after C. rodentium infection. CRACR CR - - - + CRACR - - - + CRACR One month later, the mice 1 mo 1 mo were reinfected with CR D E Rag2 / (CRACR) Rag2 / Il22 / (CRACR) (CRACR). (B) Analysis of 107 100 4 *** ILC3s (left) and IL-22+ 106 0 −/− 80 ILC3s (right) in Rag2 105 -4 *** 60 mice (n = 3 to 4). (C) Fecal 104 -8 C. rodentium counts (n = 7). 103 *** 40 102 -12 (D) Survival (left) and body *** Rag2 / 20 Rag2 / Rag2 / *** 101 Rag2 / Il22 / weight (right) in reinfected -16 Rag2 / Il22 / Rag2 / Il22 / 0 0 10 Rag2−/− and Rag2−/−IL22−/− 10 30 33 34 35 37 40 41 10 40 42 44 2 3 4 x10 1 Time (days) Time (days) mice (n = 7). (E) C. rodentium Radiance (p/sec/cm /sr) Radiance (p/sec/cm /sr) growth monitored by IVIS F G 100 5 Il22 / imaging 3 days after reinfecControl 0 +ILC3 (CR) *** 80 ILC3 tion (left). Relative C. rodentium +ILC3 (CRACR) -5 60 growth was determined in Il22 / -10 −/− −/− −/− Rag2 and Rag2 IL22 40 -15 CR Cell adoptive mice (n = 7) (right). * 20 -20 transfer ** ** (F) Experimental design for ** ** 0 -25 D0 D3 D6 D9 0 4 8 12 16 20 24 (G). ILC3s were purified from 0 3 4 5 7 9 10 11 12 13 16 18 Time (day) Time (day) infected (CR) or reinfected (CRACR) mice 3 days after infection and transferred into C. rodentium–infected Il22−/− mice. (G) Survival and body weight were assessed at the indicated times after infection [n = 4 for Il22−/− and ILC3 (CR); n = 10 for Il22−/− and ILC3 (CRACR); n = 11 for Il22−/− per group, pool of two independent experiments]. Each graph corresponds to the mean ± SEM of the values obtained. *P < 0.05, **P < 0.01, and ***P < 0.001 using Krustal-Wallis test (B), two-tailed Mann-Whitney test [(C) to (G)], or log-rank (Mantel-Cox) test [(D) and (G)].

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A

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RorcGFP Il22TdT Abx

CR D-1

D0

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CD49a+ ILC3

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CR

CRA CRACR

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C

D

Ndufa1 Ndufa2 Ndufa3 Ndufa4 Ndufa5 Ndufa6 Ndufa7 Ndufa8 Ndufa9 Ndufa10 Ndufa11 Ndufa12 Ndufab1 Ndufb2 Ndufb3 Ndufb4 Ndufb5 Ndufb6 Ndufb7 Ndufb8 Ndufb9 Ndufb10 Ndufb11 Ndufc1 Ndufc2 Ndufs1 Ndufs2 Ndufs3 Ndufs4 Ndufs5 Ndufs6 Ndufs7 Ndufs8 Ndufv1 Ndufv2 Ndufv3 Sdha Sdhb Sdhc Sdhd Uqcrb Uqcrc1 Uqcrc2 Uqcrfs1 Uqcrq Uqcr10 Uqcrh Uqcr11 Uqcrb Cox7b Cox7a2 Cox8a Cox6b1 Cox6a1 Cox6c Atp5h Atp5j2 Atp5k Atp5f1 Atp5d Atp5e Atp5g3

C CR CRA CRACR

Arg and Pro Metabolism Glycolysis TCA cycle Fatty acid metabolism Oxidative phosphorylation Pathogenic E.Coli infection Cell Cycle NK cell mediated cytotoxicity Cytokine/receptor interaction Chemokine signaling Proteasome Adherens junction Focal adhesion DNA replication

Oxphos

C CR CRA CRACR

CD49a+ ILC3

Glycolysis

Acsl1 Acsl3 Acsl4 Acsl5 Aco2 Idh2 Idh3a Idh3b Idh3g Ogdh Suclg1 Sdha Sdhb Sdhc Sdhd Fh1 Mdh1 Mdh2

Slc2a3 Pfkp Slc2a1 Pdhb Hk1 Gpi1 Pkm Pfkl Pdha1 Hk2 Aldoa Dld Adh5 Pfkfb3 Dlat G6pc3 Eno1 Akr1a1 Pck2 Ldha Aldh9a1 Aldh3a2 Pgm1 Aldh2 Ldhb Galm

CCR6+ ILC3

2 0 -2

2 0 -2

TCA cycle

CD49a+ ILC3

CD49a+ ILC3

CCR6+ ILC3

CCR6+ ILC3

1.0 1.2 1.4 1.0 1.2 1.4

NES (p5% Ns are excluded; n/a, not applicable. VOI, variant of interest; VUM, variant under monitoring.

REGN10933 REGN10987 COV2-2196 COV2-2130 LY-CoV555 LY-CoV016 CT-P59

S309

ADI58125

Total GISAID counts

Omicron counts

VOC, VOI, VUM harboring mutation

G339D 196,756 192,125 ................................................................................................................................................................................................................................................................................................................................................ S371L 182,692 179,486 ................................................................................................................................................................................................................................................................................................................................................ S373P 185,025 181,374 ................................................................................................................................................................................................................................................................................................................................................ S375F 184,990 181,461 ................................................................................................................................................................................................................................................................................................................................................ Beta, K417T K417N X X X 116,510 70,903 in Gamma ................................................................................................................................................................................................................................................................................................................................................ N440K 92,338 79,859 ................................................................................................................................................................................................................................................................................................................................................ G446S X x 83,953 80,518 ................................................................................................................................................................................................................................................................................................................................................ S477N x X x 262,216 187,081 ................................................................................................................................................................................................................................................................................................................................................ T478K X 3,976,461 187,859 Delta ................................................................................................................................................................................................................................................................................................................................................ E484K in Beta, Gamma, Mu, E484A X X X X 192,062 186,965 Iota, Eta, Zeta, Theta; E484Q in Kappa ................................................................................................................................................................................................................................................................................................................................................ Q493R X X x X x X 191,484 188,353 ................................................................................................................................................................................................................................................................................................................................................ G496S X 187,583 184,575 ................................................................................................................................................................................................................................................................................................................................................ Q498R X 188,462 185,805 ................................................................................................................................................................................................................................................................................................................................................ Alpha, Beta, N501Y 1,434,752 186,285 Theta, N501K in Mu ................................................................................................................................................................................................................................................................................................................................................ Y505H X* 188,250 185,491 ................................................................................................................................................................................................................................................................................................................................................ PDB ID 6XDG 6XDG 7L7D 7L7E 7KMG 7C01 7CM4 This study n/a ................................................................................................................................................................................................................................................................................................................................................ *For ADI-58125, the impact on binding of C, N, and S substitutions is shown at position Tyr505 according to mutagenesis studies [J. Belk et al., WO2021207597 - Compounds Specific to Coronavirus S Protein and Uses Thereof. Adagio Therapeutics Inc. (2021)].

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from neutralization mediated by a panel of NTD mAbs (7, 9). The RBD is the main target of plasmaneutralizing activity in convalescent and vaccinated individuals and comprises several antigenic sites recognized by neutralizing Abs with a range of neutralization potencies and breadth (12, 13, 21, 23–36) (Fig. 3A). Our structures provide a high-resolution blueprint of the residue substitutions found in this variant (Fig. 3B) and their impact on binding of clinical mAbs (Table 1). Several individual mutations or subsets of mutations occurring in the Omicron RBD have been reported to affect neutralizing antibody binding or neutralization (37). The K417N, G446S, S477N, T478K, E484A, Q493R, G496S, Q498R, N501Y. and Y505H mutations are part of antigenic site I, which is immunodominant in previous variants (13, 24). K417N, E484A, S477N, and Q493R would lead to loss of electrostatic interactions and steric clashes with REGN10933 whereas G446S would lead to steric clashes with REGN10987, consistent with the dampened binding to the Omicron RBD and S trimer (Fig. 3, C and D, fig. S3, and table S3) and with previous analyses of the impact of individual mutations on neutralization by each of these two mAbs (9, 38–40). Moreover, N440K was reported to dampen REGN10987 neutralization severely (9). Reduced binding of the Omicron RBD to COV2-2196 and COV2-2130, relative to the Wuhan-Hu-1 RBD, likely results from T478K [based on Delta S (2)], Q493R, and putatively S477N for COV2-2196, as well as G446S and E484A for COV2-2130 (Fig. 3, E and F, fig. S4, and table S3). Integrating these data with neutralization assays suggests that although each point mutation only imparts a

small reduction of COV2-2196– or COV2-2130– mediated neutralization (9), the constellation of Omicron mutations leads to more pronounced loss of activity (7–11). E484A abrogates electrostatic interactions with LY-CoV555 heavy and light chains, whereas Q493R would prevent binding through steric hindrance (Fig. 3G, fig. S4, and table S3), as supported by neutralization data (9). K417N is expected to negatively affect the constellation of electrostatic interactions formed between the Omicron RBD and LY-CoV16 heavy chain, thereby abolishing binding (Fig. 3H, fig. S4, and table S3) and neutralization of single-mutant S pseudoviruses (9, 40, 41). Furthermore, S477N and Q493R have been shown to dampen binding of and neutralization mediated by LYCoV16 (9, 41). Finally, K417N, E484A, and Q493R hinder CT-P59 engagement through a combination of steric hindrance and remodeling of electrostatic contacts, thereby preventing binding (Fig. 3I, fig. S4, and tables S1 and S3). The SARS-CoV-2 Omicron G339D and N440K mutations are within or near antigenic site IV, which is recognized by the S309 mAb (12). Nonetheless, relative to Wuhan-Hu-1 pseudovirus or Washington-1 authentic virus, S309 undergoes only a factor of 2 to 3 reduction of neutralizing activity against Omicron (7, 9–11). The Lys side chain introduced by the N440K substitution points away from the S309 epitope and does not affect binding. The Asp side chain introduced by the G339D substitution does not interfere with the S309 epitope, although not all rotamers are compatible with mAb binding (fig. S2). This finding likely explains the similarly moderate reduction of S309 potency against the single G339D S mu-

tant (9) or the full constellation of Omicron S mutations (7, 9–11). The modest reduction of the Omicron RBD binding to S309 (Fig. 3J, fig. S4, and table S3) mirrors the reduced neutralization potency of this VOC (by a factor of 2 to 3 relative to ancestral viruses) and concurs with deep-mutational scanning analysis of individual mutations on S309 recognition (24). Overall, the S309 binding mode remains unaltered by the Omicron mutations, including recognition of the N343 glycan (fig. S5). The Omicron RBD is structurally similar to the Wuhan-Hu-1 RBD, and both structures can be superimposed with an RMSD of 0.8 Å over 183 aligned Ca residues [as compared to PDB 6m0j (42)]. However, the region comprising residues 366 to 375, which harbors the S371L/S373P/S375F substitutions, deviates markedly from the conformation observed for the Wuhan-Hu-1 RBD, irrespective of the presence of bound linoleic acid (4, 42, 43). Although this region is weakly resolved in the cryo-EM and x-ray structures, the conformation adopted in the latter structure is incompatible with binding of some cross-reactive site II mAbs such as S2X35, consistent with our observation of dampened binding (fig. S6). We therefore propose that these mutations participate in rendering this region of the RBD dynamic and mediate immune evasion from some site II mAbs. We recently reported that the SARS-CoV-2 Omicron RBD binds human ACE2 with a factor of ~2.4 enhanced affinity relative to the Wuhan-Hu-1 RBD (7). Our crystal structure of the human ACE2-bound Omicron RBD elucidates how the constellation of RBD mutations found in this VOC affect receptor recognition

Fig. 2. SARS-CoV-2 Omicron S mutations outside the NTD and RBD. Ribbon diagram shows a cross section of the Omicron S glycoprotein (the location of this slice on the S trimer is indicated at left). Mutated residues T547K, N764K, N856K, N969K, and L981F are shown as red spheres, whereas the residues they contact are shown as spheres colored as the protomer to which they belong. Black asterisks show the positions of residues involved in the prefusion-stabilizing 2P mutations (K986P and V987P) used in all three vaccines deployed in the US. The three S protomers are colored light blue, pink, and gold. N-linked glycans are shown as dark blue surfaces.

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(Fig. 4A and table S2). The N501Y mutation alone enhances ACE2 binding to the RBD by a factor of 6 relative to the Wuhan-Hu-1 RBD, as reported for the Alpha variant (6), likely as a result of increased shape complementarity between the introduced Tyr side chain and the ACE2 Tyr41 and Lys353 side chains (Fig. 4B). Omicron S residue Tyr501 and ACE2 residue Tyr41 form a T-shaped p-p stacking interaction, as previously observed for an N501Yharboring S structure in complex with ACE2 (44). The K417N mutation dampens receptor recognition by a factor of ~3 (2, 6, 39, 45) likely through loss of a salt bridge with ACE2 Asp30 (Fig. 4C). The Q493R and Q498R mutations introduce two new salt bridges with Glu35 and Glu38, respectively, replacing hydrogen bonds formed with the Wuhan-Hu-1 RBD and thereby remodeling the electrostatic interactions with ACE2 (Fig. 4D). Both of these individual mutations were reported to reduce ACE2 binding avidity slightly by deep-mutational scanning studies of the yeast-displayed SARS-CoV-2 RBD (46). Finally, S477N leads to formation of new hydrogen bonds between the introduced Asn side chain and the ACE2 Ser19 backbone amine and carbonyl groups (Fig. 4E). Collectively, these mutations have a net enhancing effect on binding of the Omicron RBD to human ACE2 relative to Wuhan-Hu-1, which suggests that structural epistasis enables immune evasion while retaining efficient receptor engagement. The large number of Omicron mutations in the immunodominant receptorbinding motif likely explains a substantial proportion of the loss of neutralization by convalescent and vaccine-elicited polyclonal antibodies, and is in line with the known plasticity of this subdomain (24). Although the N501Y mutation has previously been described as enabling some SARSCoV-2 VOCs to infect and replicate in mice, the Alpha and Beta variant RBDs only weakly bound mouse ACE2 (47, 48). The SARS-CoV-2 Omicron RBD, however, interacts more strongly with mouse ACE2 than do the Alpha and Beta variant RBDs when evaluated side-byside (fig. S7A) and can use mouse ACE2 as an entry receptor for S-mediated entry (7, 49). We propose that the Q493R mutation plays a key role in enabling efficient mouse ACE2 binding, which occurs through formation of a new electrostatic interaction with the Asn31 side chain amide (Lys31 in human ACE2); this is supported by in silico modeling based on our human ACE2-bound crystal structure (fig. S7B). These findings concur with the emergence and fixation of the Q493K RBD mutation upon serial passaging in mice to yield a mouse-adapted virus designated SARS-CoV-2 MA10 (50). This work defines the molecular basis for the broad evasion of humoral immunity exhibited SCIENCE science.org

Fig. 3. SARS-CoV-2 Omicron RBD mutations promote escape from a panel of clinical mAbs. (A) RBD antigenic map as determined in (13). (B) Ribbon diagram of the RBD crystal structure, with residues mutated relative to the Wuhan-Hu-1 RBD shown as red spheres. The N343 glycan is rendered as blue spheres. (C to J) Zoomed-in views of the Omicron RBD (blue) superimposed on structures of clinical mAbs (gray). Selected residues that interfere with the following mAbs are circled: (C) REGN10933, (D) REGN10987, (E) COV2-2196, (F) COV2-2130, (G) LY-CoV555, (H) LY-CoV16, (I) CT-P59, and (J) S309, which does not clash with G339D. All panels were rendered with the crystal structure except (J), which was generated with the cryo-EM model. Binding of the Wuhan-Hu-1 (gray line) or Omicron (red line) RBD to the corresponding mAb was evaluated using surface plasmon resonance (single-cycle kinetics) and is shown underneath each structural superimposition. White and gray stripes are association and dissociation phases, respectively. The thin black line is a fit to a kinetic model. The decrease in affinity between Wuhan-Hu-1 and Omicron binding is indicated in red. Results are consistent with immunoglobulin G binding to S ectodomains (fig. S3). 25 FEBRUARY 2022 ¥ VOL 375 ISSUE 6583

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49. M. Hoffmann et al., Cell 10.1016/j.cell.2021.12.032 (2022). 50. S. R. Leist et al., Cell 183, 1070–1085.e12 (2020). 51. Y. Weisblum et al., eLife 9, e61312 (2020). 52. A. C. Walls et al., Cell 184, 5432–5447.e16 (2021). 53. A. C. Walls et al., Cell 183, 1367–1382.e17 (2020). 54. P. S. Arunachalam et al., Nature 594, 253–258 (2021). 55. D. R. Martinez et al., Science 373, 991–998 (2021). 56. A. A. Cohen et al., Science 371, 735–741 (2021). ACKN OW LEDG MEN TS

Fig. 4. Molecular basis of human ACE2 recognition by the SARS-CoV-2 Omicron RBD. (A) Ribbon diagram of the crystal structure of the Omicron RBD in complex with the ACE2 ectodomain. The S309 and S304 Fab fragments are not shown for clarity. (B to E) Zoomed-in views of the RBD-ACE2 interface. highlighting modulation of interactions due to introduction of the N501Y (B), K417N (C), Q493R/Q498R (D), and S477N (E) residue substitutions.

by SARS-CoV-2 Omicron and underscores the SARS-CoV-2 S mutational plasticity as well as the importance of targeting conserved epitopes in the design and development of vaccines and therapeutics. The S309 mAb (the parent of sotrovimab) neutralizes Omicron with one-half to one-third the potency with which it neutralizes Wuhan-Hu-1 or Washington-1, whereas the seven other clinical mAbs or mAb cocktails undergo reduction of neutralizing activity of one to two orders of magnitude or greater. Furthermore, some Omicron isolates (≈9%) harbor the R346K substitution, which, in conjunction with N440K (present in the main haplotype), leads to escape from C135 mAb-mediated neutralization (25, 51). R346K does not affect S309 whether in isolation or in the context of the full constellation of Omicron mutations; hence, mAbs targeting antigenic site IV can be differently affected by Omicron (7, 9, 46). Whereas C135 was identified from a SARS-CoV-2 convalescent donor (25), S309 was isolated from a subject who recovered from a SARS-CoV infection in 2003 (12); the latter strategy increased the likelihood of finding mAbs that recognize epitopes that are mutationally constrained throughout sarbecovirus evolution. The identification of broadly reactive mAbs that neutralize multiple distinct sarbecoviruses, including SARSCoV-2 variants, paves the way for designing vaccines that elicit broad sarbecovirus immunity (52–56). These efforts offer hope that the same strategies that contribute to solving the current pandemic will prepare us for possible future sarbecovirus pandemics. RE FE RENCES AND N OT ES

1. R. Viana et al., Nature 10.1038/s41586-022-04411-y (2022). 2. M. McCallum et al., Science 374, 1621–1626 (2021).

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Funding: Supported by National Institute of Allergy and Infectious Diseases grants DP1AI158186 and HHSN272201700059C (D.V.), a Pew Biomedical Scholars Award (D.V.), an Investigators in the Pathogenesis of Infectious Disease Awards from the Burroughs Wellcome Fund (D.V.), Fast Grants (D.V.), NIH grant S10OD032290 (D.V.), the University of Washington Arnold and Mabel Beckman Cryo-EM Center, and Wellcome Trust grant 209407/Z/17/Z. D.V. is an Investigator of the Howard Hughes Medical Institute. Beamline 4.2.2 of the Advanced Light Source, a US DOE Office of Science User Facility under contract DE-AC0205CH11231, is supported in part by the ALS-ENABLE program funded by National Institute of General Medical Sciences grant P30 GM124169-01. For the purpose of open access, the author has applied a CC BY public copyright license to any Author Accepted Manuscript version arising from this submission. Author contributions: M.M., J.E.B., A.C.W., H.W.V., D.C., G.S., and D.V. conceived the project; M.M., L.E.R., S.K.Z., G.S., and D.V. designed experiments; M.M., N.C., S.K.Z., J.E.B., A.J., J.R.D., and A.E.P. expressed and purified proteins; L.E.R. and J.R.D. performed SPR analysis; S.K.Z. performed biolayer interferometry analysis; M.M. carried out cryo-EM sample preparation, data collection, and processing; M.M. and D.V. carried out cryo-EM model building and refinement; N.C. and J.R.D. carried out crystallization experiments; J.N. collected and processed x-ray diffraction data; M.M., T.I.C., G.S., and D.V. built and refined the crystal structure; and M.M. and D.V. wrote an initial draft of the manuscript with input from all authors. Competing interests: N.C., L.E.R., J.R.D., A.E.P., H.W.V., D.C., and G.S. are employees of Vir Biotechnology Inc. and may hold shares in Vir Biotechnology Inc. D.C. is currently listed as an inventor on multiple patent applications, which disclose the subject matter described in this manuscript. A.C.W., G.S., D.C., and D.V. are listed as inventors on patent 49230.03US1 describing the S309 epitope. H.W.V. is a founder and hold shares in PierianDx and Casma Therapeutics. Neither company provided resources. The Veesler laboratory has received a sponsored research agreement from Vir Biotechnology Inc. T.C.’s contribution was made under terms of a paid consultancy from Vir Biotechnology Inc. The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest. Data and materials availability: The cryo-EM map and coordinates have been deposited to the Electron Microscopy Databank and Protein Data Bank with the following accession numbers: 2 open/1 closed RBD EMD-25993; 2 closed/1 open RBD EMD-25992, EMD-25990, EMD-25991, PDB numbers 7TM0, 7TLY, 7TLZ. The crystal structure has been deposited to the Protein Data Bank with accession number 7TN0. Materials generated in this study will be made available on request, but we may require a completed materials transfer agreement signed with Vir Biotechnology or the University of Washington. This work is licensed under a Creative Commons Attribution 4.0 International (CC BY 4.0) license, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. To view a copy of this license, visit https://creativecommons.org/licenses/by/4. 0/. This license does not apply to figures/photos/artwork or other content included in the article that is credited to a third party; obtain authorization from the rights holder before using such material.

SUPPLEMENTARY MATERIALS

science.org/doi/10.1126/science.abn8652 Materials and Methods Figs. S1 to S7 Tables S1 to S3 References (57–77) 24 December 2021; accepted 20 January 2022 Published online 25 January 2022 10.1126/science.abn8652

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ORGANIC CHEMISTRY

Deracemization through photochemical E/Z isomerization of enamines Mouxin Huang1†, Long Zhang1,2†, Tianrun Pan1, Sanzhong Luo1,2* Catalytic deracemization of a-branched aldehydes is a direct strategy to construct enantiopure a-tertiary carbonyls, which are essential to pharmaceutical applications. Here, we report a photochemical E/Z isomerization strategy for the deracemization of a-branched aldehydes by using simple aminocatalysts and readily available photosensitizers. A variety of racemic a-branched aldehydes could be directly transformed into either enantiomer with high selectivity. Rapid photodynamic E/Z isomerization and highly stereospecific iminium/enamine tautomerization are two key factors that underlie the enantioenrichment. This study presents a distinctive photochemical E/Z isomerization strategy for externally tuning enamine catalysis.

C

arbonyl transformations are textbook chemical reactions, and subjecting them to asymmetric catalysis can provide enantiomerically pure products essential to pharmaceutical applications (1, 2). Most of these methods involve stereogenic C–C/C–X bond formations featuring enol(ate)or enamine-based processes, in which the geometry of the intermediate and associated facial selectivity during bond formation dictate the stereoselectivity (Fig. 1A) (3, 4). In the construction of enantiopure a-tertiary carbonyls, catalytic deracemization is arguably the most atom-economical strategy (5). However, this transformation remains elusive despite tremendous progress in steering stereogenic carbonyl reactivity more generally (6, 7). The challenges are threefold. First, deracemization is inherently endergonic with a negative entropy change. In addition, according to the principle of microscopic reversibility (8), the backward and forward pathways are identical for a given chiral catalyst cycle. Hence, the degree of enantioenrichment of the starting material cannot be adjusted without exogenous chemical or physical inputs (Fig. 1A). Recent seminal works by Bach (9, 10) and Knowles and Miller (11) have demonstrated that light absorption can supply the necessary external perturbation to surmount the thermodynamic and kinetic constraints. Accordingly, photomediated energy transfer and electron transfer were found to work effectively in tandem with chiral catalysts to facilitate enantioselective deracemization of allenes or cyclic ureas, respectively (Fig. 1B). The final challenge is that a-tertiary carbonyls are easily racemized through undesired alternative pathways, adding a potentially complex time constraint to catalytic deracemization strategies (12, 13). Bearing these challenges in mind, we report a photochemical E/Z isomerization strategy 1

Center of Basic Molecular Science, Department of Chemistry, Tsinghua University, Beijing 100084, China. 2Haihe Laboratory of Sustainable Chemical Transformations, Tianjin 300192, China.

*Corresponding author. Email: [email protected] These authors contributed equally to this work.

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for the deracemization of a-branched aldehydes by using simple aminocatalysts and readily available photosensitizers (Fig. 1C). Photoisomerization was found to perturb the E/Z distribution of the in situ generated enamine intermediates. This photochemical strategy together with our previous finding (14, 15), that enamine of certain configuration (E or Z) could be stereospecifically formed from the corresponding enantiopure aldehyde with chiral primary amine catalysts such as 1a, makes possible a highly enantioselective deracemization process. Although visible light– promoted E/Z isomerization of double bonds has been widely applied in chemical (16) and materials science (17), such a process with a transient catalytic intermediate in the pursuit of stereoselective catalysis has not been reported. Photochemical tuning of enamine intermediates has been explored in pioneering studies by MacMillan (18, 19) and Melchiorre (20, 21) using photoinduced electron transfer, which greatly expanded the capacity of nucleophilic enamine catalysis. Our current strategy complements these known processes by harnessing the E/Z photoisomerization of an enamine double bond. We first investigated the deracemization of 2-phenylpropionaldehyde 2a using a chiral primary amine catalyst (14). Screening of photocatalysts showed large variations of optical enrichment outcomes (table S3), and Ir(ppy)3 was identified as the optimal one. The addition of a weak acid such as benzoic acid could significantly improve the enantioselectivity (table S1, entry 2), which is consistent with our previous finding on stereoselective enamine protonation (15). With Ir(ppy)3, benzoic acid, and primary-tertiary amine (S)-1a/HNTf2, the deracemization proceeded rapidly in 1 hour to afford (R)-2a in 77% yield (73% isolated yield) and 94% enantiomeric excess (ee). Control experiments indicated that aminocatalyst, photocatalyst, and light irradiation were all essential, and their absence led to no enrichment or rather poor enantioselectivity (table

S1, entry 1 versus entries 3 and 4). The minor yet noticeable enantioselectivity observed under thermodynamic conditions (table S1, entries 3 and 4) could be accounted for by considering kinetic resolution through selective trapping of aldehyde by aminocatalyst (~10%) (figs. S12 and S13). A small extent of homo-coupling side-reaction (~3%), (fig. S11) was also observed, which may explain the loss of aldehyde during deracemization. We next examined the reactions with optically pure aldehydes. Both (R)- and (S)-2a led to (R)-selectivity with comparable enantioselectivity (table S1, entries 7 and 8). By contrast, racemization was observed without light irradiation in these cases. This observation strongly suggests that light supplies the major driving force for the current deracemization reaction. Addition of E-stilbene or the presence of ambient oxygen, well-known energy transfer quenchers, completely inhibited the deracemization (table S1, entries 5 and 6), which is a strong indication of the energy transfer mechanism. The scope of this deracemization was next examined (Fig. 2A). 2-Arylpropanals bearing alkyl or aryl groups on the aromatic ring— such as Me, i-Bu, and Ph (2a-e)—gave high enantioselectivities. A 5-mmol-scale reaction of 2a was also successful. The enantioenriched aldehydes can be isolated by simply filtering through a pad of silica gel without ee erosion (table S6 and figs. S2 and S3). Both electron-deficient substituents—such as halogen, trifluoromethyl, and ester (2f-m)—and electrondonating groups—such as alkoxyl, aryloxy, and methylenedioxy (2n-s)—gave consistently high enantioselectivity. Functional groups such as methylthio (2t) and dimethylamino (2u) also worked well. When aldehyde and ketone functionality coexisted in the same compound, deracemization would occur preferentially at the a-carbon of the aldehyde, whereas ketone moiety remained unchanged (2v). Expanding the aromatic ring or increasing the size of the branched chain led to a slight reduction of enantioselectivity (2w-aa). The deracemization could also be applied to complex arylaldehydes bearing functional groups such as amides and alkynes (2ab and 2ac) and distinct chiral centers as in steroids and amino acids (2ad and 2ae). a-Heteroaromatic groups—such as thiophene, dibenzofuran, and pyridine— were compatible with good to excellent enantioselectivity (2af-ah). Aldehydes other than 2arylacetaldehyde showed low enantioenrichment (2ai), which we rationalized on the basis of the need for an aryl alkene chromophore in the enamine to achieve effective photoisomerization (22). a-Branched ketones were also examined but unfortunately showed no enantioenrichment (2aj and 2ak). We executed simple oxidation of selected products to obtain nonsteroidal anti-inflammatory drug compounds without loss of enantiopurity. The aldehydes could also 25 FEBRUARY 2022 • VOL 375 ISSUE 6583

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Fig. 1. Deracemization strategies. (A) Asymmetric carbonyl transformation. (B) Prior works on photocatalytic deracemization. (C) Deracemization of a-branched aldehydes through photochemical E/Z isomerization of enamine intermediate.

undergo reduction and condensation while maintaining enantiopurity (Fig. 2B). In our deracemization process, the photochemical perturbation may proceed through electron transfer (followed by hydrogen transfer) or energy transfer–induced isomerization. The oxidation potential of the E- or Z-enamine intermediate was determined to be 0.73 V (23), and Ir(ppy)3 has E1/2PC+/PC* = 0.31 V. Although photoinduced electron transfer between enamine and photocatalyst is possible, this was discounted because the obtained enantioselec870

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tivity seemed uncorrelated with the excitedstate redox potential but rather correlated with the triplet state energy (ET), as revealed in the screening of different photocatalysts (Fig. 3A). High enantioselectivity was generally obtained by using photocatalysts with triplet-state energies in the 56 to 59 kcal/mol range, which is in line with the triplet-state energy of an enamine intermediate, 54.2 kcal/mol as determined with density functional theory (DFT) calculation (Fig. 4B). The observed inhibition effect with typical triplet-state quenchers such

as stilbene or oxygen provides further support for an energy transfer mechanism (table S1, entries 5 and 6). Stoichiometric experiments were conducted to examine the enamine formation by means of nuclear magnetic resonance (NMR) spectroscopy (Fig. 3D and figs. S15 to S18). The joint use of a strong acid HNTf2 and a weak benzoic acid could significantly enhance the rate of iminium-enamine tautomerization, as previously reported (fig. S15) (14). In the presence of (S)-1a/HNTf2, (S)-2a selectively science.org SCIENCE

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Fig. 2. Substrate scope and synthetic application. (A) Substrate scope. Reactions were performed on a 0.2-mmol scale. The yields are of isolated material after purification. The ee values were determined with high-performance liquid chromatography with the isolated products. *Ir(F-ppy)3 instead of Ir(ppy)3. †(S)-1b/HOTf instead of (S)-1a/HNTf2. ‡The ee values were corresponding to the diastereomers as listed, respectively. §Reaction time was 2 hours. ¶CH2Cl2 instead of MeCN as the solvent. #Ir(F-ppy)3 instead of Ir(ppy)3. **The amount of benzoic acid was 15 mol % instead of 3 mol %. (B) Synthetic application. Reactions were performed on a 0.5-mmol scale. SCIENCE science.org

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Fig. 3. Mechanistic experiments. (A) Investigation of the performance of various photosensitizers. *Eox value instead of E1/2PC+/PC*. (B) Monitoring the ratio of E/Z-enamine by means of in situ irradiation in NMR spectrometer. The starting material was preequilibrated to attain an equilibrium ratio of E/Zenamine. Conditions were (S)-1a/HNTf2 (0.067 M), 2a (0.067 M), benzoic acid (20 mol %), and Ir(ppy)3 (2.5 mol %) in 0.6 mL MeCN-d3, preequilibrated for

formed E-enamine, equilibrating at about 50% conversion (Fig. 3D, a), whereas (R)-2a preferentially gave Z-enamine, which was equilibrated at rather lower conversion (~5%) (Fig. 3D, b), after which overriding formation of E-enamine was observed. We also examined enamine formation with rac-2a, showing a similar kinetic profile to that of (S)-2a, with E-enamine as the major isomer (E/Z = 30:1, equilibrated at ~35% conversion) (Fig. 3D, c). These results suggested that (S)-2a and (S)-1a are stereochemically matched with each other, and their coupling led to the formation of E-enamine, which is favored both thermodynamically and kinetically. Moreover, enamine isomerization was investigated with an in situ irradiative NMR experiment. A 405-nm laser beam was directed into a preequilibrated reaction mixture inside the NMR spectrometer by means of optical fiber. E-enamine was found to isomerize into Z-enamine rapidly, and a photostationary state was reached within 3 min with a E/Zenamine ratio maintained at 1.7:1 or 4:1, depending on the presence of acid additive (Fig. 3B). A quenching study verified that the excited photocatalyst could be selectively quenched by enamine (figs. S25 to S27). We 872

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10 hours then exposed to 405-nm laser irradiation inside NMR spectrometer for 20 min. Details are in the supplementary materials (figs. S19 to S23). (C) Time-course profile for deracemization under the standard conditions. (D) Monitoring the enamine formation process by NMR (a) with (S)-2a; (b) with (R)-2a; and (c) with rac-2a. Conditions were (S)-1a/HNTf2 (0.067 M) and 2a (0.067 M) in 0.6 mL MeCN-d3, with PhCOOBn as the internal standard.

also tracked the reaction progress for deracemization of 2a, and a photodynamic equilibrium could be established in 1 hour with 94% ee (Fig. 3C). Similar behaviors were observed with other substrates such as 2f, 2h, 2w, 2y, and 2aa (figs. S6 to S10). The enantioselectivity did not change upon extending irradiation, but turning off the light source led to immediate racemization (figs. S28 to S30). This observation indicated that the deracemization was driven by photochemical enamine isomerization. We further rationalized the mechanism with DFT calculations. On the basis of previous work, a weak acid-bridged proton transfer pathway was proposed to account for the iminium-enamine tautomerization (24). We calculated all four possible transition states (TS 1 to 4) that lead to E- and Z-enamine (Fig. 4A). The calculations predicted that (S)-2a would form E-enamine selectively (TS1 versus TS2) with DDG21 = 4.6 kcal/mol, whereas (R)-2a showed moderate preference for Zenamine (TS3 versus TS4) with DDG43 = 1.2 kcal/mol. These results are fully consistent with the experimentally observed kinetic profile of enamine formation (Fig. 3D). According to the principle of microscopic reversibility (8), the backward enamine protonation may pro-

ceed by means of TS1 and TS4 for E-enamine and TS2 and TS3 for Z-enamine: Both processes show the same selectivity with DDG41 and DDG32, both equal to 2.9 kcal/mol. Hence, the protonation of E- or Z-enamine should proceed with high facial selectivity to produce (S)-2a or (R)-2a, respectively. The vertical excitation energies (S0 → T1) for E/Z enamine were calculated to be 71.8 and 74.6 kcal/mol, favoring excitation of E-enamine (Fig. 4B). The preferential excitation of E-enamine over Z-enamine could be explained by the deconjugation of the b-enaminyl phenyl group in the Z-geometry because of steric hindrance. Recently, a similar deconjugation effect has also been observed in visible light–promoted isomerization of E-alkenes to their thermodynamically disfavored Z-isomers (25–27). On the basis of the mechanistic investigations above, a plausible mechanism for optical enrichment was proposed (Fig. 4C). Under the ground state, the stereochemically matched enantiomer forms a dominant E-configured enamine, which is continuously isomerized to its disfavored Z-isomer through photocatalytic energy transfer. Facially selective protonation of the Z-enamine then delivers the mismatched enantiomer. Hence, the consumption of the science.org SCIENCE

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Fig. 4. DFT simulation studies and proposed mechanism. (A) Calculated energetics of enamine formation process. (B) Calculated energetics of enamine isomerization process. (C) Proposed mechanism.

matched enantiomer and accumulation of the mismatched enantiomer are sustained to facilitate effective deracemization. In this process, the stereospecificity of enamine protonation by chiral primary aminocatalysis is also a critical determinant for effective optical enrichment. RE FE RENCES AND N OT ES

1. S. E. Denmark, J. R. Heemstra Jr., G. L. Beutner, Angew. Chem. Int. Ed. 44, 4682–4698 (2005). 2. B. Schetter, R. Mahrwald, Angew. Chem. Int. Ed. 45, 7506–7525 (2006).

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11. N. Y. Shin, J. M. Ryss, X. Zhang, S. J. Miller, R. R. Knowles, Science 366, 364–369 (2019). 12. F. Agbossou, J.-F. Carpentier, A. Mortreux, Chem. Rev. 95, 2485–2506 (1995). 13. J. Burés, A. Armstrong, D. G. Blackmond, Chem. Sci. 3, 1273–1277 (2012). 14. L. Zhang, N. Fu, S. Luo, Acc. Chem. Res. 48, 986–997 (2015). 15. N. Fu, L. Zhang, J. Li, S. Luo, J. P. Cheng, Angew. Chem. Int. Ed. 50, 11451–11455 (2011). 16. V. García-López, D. Liu, J. M. Tour, Chem. Rev. 120, 79–124 (2020). 17. H. K. Bisoyi, Q. Li, Chem. Rev. 116, 15089–15166 (2016). 18. D. A. Nicewicz, D. W. MacMillan, Science 322, 77–80 (2008). 19. M. T. Pirnot, D. A. Rankic, D. B. Martin, D. W. MacMillan, Science 339, 1593–1596 (2013).

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20. E. Arceo, I. D. Jurberg, A. Alvarez-Fernández, P. Melchiorre, Nat. Chem. 5, 750–756 (2013). 21. M. Silvi, E. Arceo, I. D. Jurberg, C. Cassani, P. Melchiorre, J. Am. Chem. Soc. 137, 6120–6123 (2015). 22. J. B. Metternich, R. Gilmour, Synlett 27, 2541–2552 (2016). 23. Y. Li, D. Wang, L. Zhang, S. Luo, J. Org. Chem. 84, 12071–12090 (2019). 24. Y. Zhu, L. Zhang, S. Luo, J. Am. Chem. Soc. 138, 3978–3981 (2016). 25. K. Singh, S. J. Staig, J. D. Weaver, J. Am. Chem. Soc. 136, 5275–5278 (2014). 26. J. B. Metternich, R. Gilmour, J. Am. Chem. Soc. 137, 11254–11257 (2015). 27. J. J. Molloy et al., Science 369, 302–306 (2020).

ACKN OWLED GMEN TS

We thank J. Cheng, X. Guo, and L. Jiao for helpful discussions. Funding: This work is supported by the Natural Science Foundation of China (91956000, 22031006, and 21861132003), Tsinghua University Initiative Scientific Research Program, and Haihe Laboratory of Sustainable Chemical Transformations. We thank the Tsinghua Xuetang Talents Program for computational support. L.Z. is supported by the National Program of Top-notch Young Professionals. Author contributions: S.L. conceived and directed the project. M.H. conducted the experiments, with the help of T.P.; L.Z. performed the computational studies. M.H. and S.L. wrote the manuscript, with contributions from all authors. Competing interests: The authors declare that they have no competing interests. Data and

materials availability: All data are available in the main text or the supplementary materials. SUPPLEMENTARY MATERIALS

science.org/doi/10.1126/science.abl4922 Materials and Methods Supplementary Text Figs. S1 to S33 Tables S1 to S7 References (28–52) 16 July 2021; resubmitted 4 November 2021 Accepted 25 January 2022 10.1126/science.abl4922

BLACK HOLES PD (%)

Black hole spinÐorbit misalignment in the x-ray binary MAXI J1820+070

6 5

1

4

The observational signatures of black holes in x-ray binary systems depend on their masses, spins, accretion rate, and the misalignment angle between the black hole spin and the orbital angular momentum. We present optical polarimetric observations of the black hole x-ray binary MAXI J1820+070, from which we constrain the position angle of the binary orbital. Combining this with previous determinations of the relativistic jet orientation, which traces the black hole spin, and the inclination of the orbit, we determine a lower limit of 40° on the spin-orbit misalignment angle. The misalignment must originate from either the binary evolution or black hole formation stages. If other x-ray binaries have similarly large misalignments, these would bias measurements of black hole masses and spins from x-ray observations.

B

lack holes can be characterized with just two parameters: mass and spin. When a black hole resides in a binary system, accreting material from a companion donor star through the accretion disk, there are additional parameters that determine its observational signatures: the mass accretion rate and the misalignment angle between the black hole spin and the orbital axis. Standard methods to measure black hole spin from x-ray observations—iron line spectroscopy (1) or modeling of the accretion disk spectrum (2)—assume that the misalignment angle is small. Conversely, the standard inter1

Department of Physics and Astronomy, FI-20014 University of Turku, Finland. 2Space Research Institute (IKI) of the Russian Academy of Sciences, 117997 Moscow, Russia. 3 Nordic Institute for Theoretical Physics (Nordita), KTH Royal Institute of Technology and Stockholm University, SE-10691 Stockholm, Sweden. 4Leibniz-Institut für Sonnenphysik, 79104 Freiburg, Germany. 5Astrophysics Research Institute, Liverpool John Moores University, L3 5RF Liverpool, UK. 6Department of Astrophysics, Institute for Mathematics, Astrophysics and Particle Physics (IMAPP), Radboud University, NL-6500 GL Nijmegen, Netherlands. 7 Space Research Organisation of the Netherlands (SRON), Netherlands Institute for Space Research, NL-2333, CA Leiden, Netherlands. 8Centro de Astrobiología, Villanueva de la Cañada, S-28692 Madrid, Spain. 9Department of Physics and Astronomy, University of Denver, Denver, CO 80208, USA. 10Instituto de Astrofísica de Canarias, E-38205 La Laguna, Tenerife, Spain. 11Departamento de Astrofísica, Universidad de La Laguna, E-38206 La Laguna, Tenerife, Spain. *Corresponding author. Email: [email protected]

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pretation of low-frequency quasi-periodic oscillations in x-ray and optical observations of black hole x-ray binaries as precession of the accretion disk (3–5) requires the assumption that the misalignment angle is non-negligible. Substantial misalignment is theoretically predicted for x-ray binaries that received high velocities during formation (6). The misalignment angle must be inherited from the formation process, because it can only decrease when the black hole is accreting (7). Gravitational wave observations of merging black holes have detected signatures of orbital precession (8), indicating nonzero misalignment in these systems (9), though they might not be representative of the wider population. Measuring the misalignment angle in x-ray binaries requires determining the threedimensional orientation of the black hole spin and orbital axis. Accreting black holes often show relativistic jets, which are launched along an axis determined by the black hole spin direction (10). The jet inclination angle can be directly obtained in some cases from radio observations (11), whereas the jet position angle can be measured using either radio or x-ray imaging. Combining these two angles allows the black hole spin orientation to be determined. Orbital parameters such as period and orbital inclination can be determined

PA (deg)

1,3,2

3 2 1 0

Juri Poutanen *, Alexandra Veledina , Andrei V. Berdyugin , Svetlana V. Berdyugina , Helen Jermak5, Peter G. Jonker6,7, Jari J. E. Kajava1,8, Ilia A. Kosenkov1, Vadim Kravtsov1, Vilppu Piirola1, Manisha Shrestha5,9, Manuel A. Perez Torres10,11, Sergey S. Tsygankov1,2 1,2,3

A

4

B

10 0 -10 -20 -30 -40 0.0

0.2

0.4 0.6 0.8 1.0 Phase Fig. 1. Observed optical polarization properties of MAXI J1820+070. (A) Intrinsic PD and (B) PA of MAXI J1820+070 during quiescence are shown as a function of orbital phase (using a published ephemeris) (23). The intrinsic values were obtained from the observed ones by subtracting the foreground interstellar polarization, which is measured from nearby field stars. Blue circles, green triangles, and red squares correspond to the B, V, and R bands, respectively, with error bars showing the 68% confidence levels. Polarization is strongest in the B band and weakest in the R band, although the angle does not change substantially.

using spectroscopic measurements of radial velocities of the donor star taken during quiescence, the stage at which accretion to the black hole is reduced and optical emission is not dominated by the accretion disk, through orbital modulation of the optical photometry and using constraints from the presence or absence of x-ray and optical disk eclipses (12). The black hole x-ray binary MAXI J1820+070 was discovered as a transient x-ray source on 11 March 2018 (13). X-ray quasi-periodic oscillations detected shortly after this discovery were observed for >100 days (14). Ejections of material traveling at relativistic velocities have been observed from this source in both radio and x-rays, indicating that the jet inclination (measured from the line of sight) is ijet ¼ 63°T3° and the position angle (measured on the plane of the sky from north to east) is qjet ¼ 25:° 1T1:° 4 (15–17). Both angles were determined to be stable over the observed science.org SCIENCE

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duration of the outburst. The orbital inclination has been constrained to the range 66° < iorb < 81° by the lack of x-ray eclipses and the detection of grazing optical eclipses (12). Determination of the orientation of the orbital axis requires one further parameter, the orbital position angle qorb . We monitored MAXI J1820+070 in the optical B, V, and R photometric bands using double image polarimeters (18, 19) during the 2018 outburst and quiescence. We obtained the source intrinsic linear polarization by subtracting the foreground interstellar polarization, measured from nearby field stars. During the outburst, when the relativistic jets were detected at radio frequencies, the intrinsic linear polarization degree (PD) in the V and R bands reached 0.5% at a polarization angle [(PA), also measured from north to east)] of 23° to 24°, which coincides with the jet position angle within the uncertainties (20, 21). After the source faded in the x-rays, the PD increased by a factor of 5 to 10 and the PA changed by 40°T4° to 17°T4° (Fig. 1 and table S1) (22). This increase in PD is most prominent in the B band, which also has the highest PD in the range 1.5 to 5%, whereas the R-band polarization changes from 0.4 to 2%. The PA is most precisely determined in the B band, which 1.0

Flux Fν (mJy)

z

LT i r V

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Swift / UVOT U W1 M2 W2

0.3

0.1

3 1014

1015 Frequency ν (Hz)

2 1015

Fig. 2. Spectral energy distribution. The average spectral energy distribution (SED) of MAXI J1820+070 (red diamonds) as observed with the Liverpool Telescope (LT) and Swift UVOT in July 2020 and corrected for reddening, with color excess EðB V Þ ¼ 0:29. The photometric bands are indicated at the top of the figure. The black dotted lines give the lower and upper limits on the flux for lower and higher extinction with EðB V Þ ¼ 0:25 and 0:325, respectively. The polarized flux divided by the best-fitting model polarization degree PUV = 0.055 (i.e., multiplied by a factor of ~18) is indicated by blue triangles. Error bars show 68% confidence levels. The solid black line gives the total model flux consisting of the companion star modeled as a blackbody (pink dot-dashed line), accretion disk (red dotted line), and a hot blackbody (blue dashed line). The spectrum of a K7 star (24) is shown for comparison (solid green line). SCIENCE science.org

also shows the least variability, with the mean being hPA i ¼ 19:° 7T1:° 2. We identify three properties of the quiescentstate polarization: (i) It is strongest in the blue part of the optical, with approximate dependence on frequency n as PD(n) ¼ n3 (Fig. 2 and table S1); (ii) the PD remains high in the range 0.5 to 5% and the PA is stable; and (iii) the PA undergoes apparently stochastic variations with an amplitude of 0.9; table S10, tab 2]. Additionally, we compared effector and dysfunctional gene sets consisting of different minimal combinations of classical T cell activation or dysfunction markers (ENTPD1, CXCL13, PDCD1, ITGAE,

TIGIT, TOX, LAG3, HAVCR2, and GZMK; table S10, tab 3) for their ability to capture CD4+ and CD8+ NeoTCRs. Gene sets that contain CXCL13 performed well in capturing CD4+ NeoTCR cells (AUC > 0.8) but were inferior (AUC ≤ 0.8) to the NeoTCR8 signature in predicting CD8+ NeoTCRs. Notably, versions of the NeoTCR4 and NeoTCR8 signatures that intentionally excluded these nine genes demonstrated high sensitivity and specificity (NeoTCR4 AUCs > 0.8 and NeoTCR8 science.org SCIENCE

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Tumor 4393 NeoTCR Signature

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NeoTCR8sig NeoTCR4sig

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NeoTCR8sig NeoTCR4sig

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Vetted NeoTCRs n = 15

NeoTCR Signature Performance CD4 Validation

CD8 Validation

AUC

AUC

CD8 CD8

Tumor 4400

F

Vetted NeoTCRs

NeoTCR Signature

n = 29 CD4

NeoTCR8sig NeoTCR4sig

Vetted NeoTCRs

n = 77

CD8

Tumor Screen

CD4 CD8

C

CD8 Neoepitope Parse

D

Tumor Antigen Screen

G

Tumor 4421 NeoTCR Signature

Vetted NeoTCRs

NeoTCR8sig NeoTCR4sig

n = 82 CD8

Distinct Clones per patient / Cluster

100

Fig. 3. NeoTCR signatures enable prospective identification of neoantigen-, tumor-associated antigen-, and tumor-reactive CD4 and CD8 TCRs from newly resected tumors. (A) (Top) Transcriptomic map of 630 TILs sequenced from tumor 4393 (colon). Cells that score in the 95th percentile of NeoTCR4 and NeoTCR8 signatures are highlighted. (Bottom) Experimentally verified CD4+ and CD8+ NeoTCR-expressing cells (n = 29) backprojected onto a transcriptomic map (black). (B) (Top) Screening of eight predicted candidate CD8+ TCRs and six candidate CD4+ TCRs against peptide pools and TMGs that represent 156 tumor mutations identified four TMG- and peptide pool–reactive CD8+ TCRs and three TMG- and peptide pool–reactive CD4+ TCRs. TMGs are shown for clarity. (Bottom) Screening of CD8+ TCRs against corresponding autologous tumors demonstrated selective reactivity toward autologous (Auto.) tumors relative to allogeneic (Allo.) tumors by 7 of 8 TCRs. The right axis, which shows the percentage of activated TCR transduced cells, refers to cells expressing 4-1BB as determined by flow cytometry. (C) Reactivity deconvolution data of the TMG-reactive CD8+ TCRs against constituent peptides of their reactive TMGs for newly identified TCRs from tumor 4393. CD8+ TCRs reactive to TMG1 (TCRs DB1, DB2, DB3, and E) demonstrated reactivity to FAM63Amut (p.D460N). (D) Screening of neoantigen–nonreactive TCRs from tumor 4393 against autologous dendritic cells expressing TAA RNA or pulsed with TAA peptide pools identified tumor 4393 CD4 TCR D as reactive toward MAGEA6. (E) (Left) Transcriptomic map of 2972 TILs sequenced from tumor 4394 (colon).

AUCs > 0.9; table S10, tab 4). These data together suggest that the TIL dysfunctional program identified here is not limited to just a few known exhaustion or activation genes but also includes several genes with yet-unidentified SCIENCE science.org

NeoTCR4 0.842

150

50

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NeoTCR8 0.934

Sensitivity

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# Of Distinct Clones Per 1000 Sequenced TILs

CD4

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CD8-NeoTCR CD4-NeoTCR Cluster Cluster

1-Specificity

Cells that score in the 95th percentile of NeoTCR4 and NeoTCR8 signatures are highlighted. (Right) Experimentally verified CD8+ NeoTCR-expressing cells (n = 15) backprojected onto a transcriptomic map. (F) (Left) Transcriptomic map of 2559 TILs sequenced from tumor 4400 (colon). Cells that score in the 95th percentile of NeoTCR4 and NeoTCR8 signatures are highlighted. (Right) Experimentally verified CD4+ and CD8+ NeoTCR-expressing cells (n = 77) backprojected onto a transcriptomic map. (G) (Left) Transcriptomic map of 10,049 TILs sequenced from tumor 4421 (colon). Cells that score in the 98th percentile of NeoTCR4 and NeoTCR8 signatures are highlighted. (Right) Experimentally verified CD4+ and CD8+ NeoTCR-expressing cells (n = 82) backprojected onto a transcriptomic map. (H) AUC scores showing the sensitivity and specificity of NeoTCR4, NeoTCR8, and published signatures in calling verified tumor- and neoantigen-reactive TCRs from prospective tumor samples. scGSEA was performed on T cells from samples 4393, 4394, 4400, and 4421, and ROC curves were generated to compare signature sensitivity and specificity. AUC values of all signatures were ranked by their ability to call CD4+ NeoTCRs (top left) and CD8+ NeoTCRs (top right). Selected signatures of interest are highlighted. (Bottom) ROC curves of highest-scoring signatures for CD4 (NeoTCR4; left) and CD8 (NeoTCR8; right) NeoTCRs. (I) Dot plots showing numbers of clones present in the C1 NeoTCR4 and C6 NeoTCR8 states per tumor from Fig. 1A, normalized to 1000 sequenced T cells for each tumor. Bars denote median values.

functions that together establish a recurrent dysfunctional transcriptional module within neoantigen-specific TILs from human cancers. Correlation analyses of the NeoTCR4 and NeoTCR8 gene signatures demonstrated that

the NeoTCR4 signature was most similar to those of the lung cancer TIL signatures Caushi. CD4.Tfh.2 [Pearson’s correlation coefficient (r) = 0.725] and Wu.CD4.IL6ST (Pearson’s r = 0.612), whereas the NeoTCR8 signature was most 25 FEBRUARY 2022 • VOL 375 ISSUE 6583

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similar to those of exhausted CD8 cells observed in basal and squamous cell carcinoma (Yost.CD8.Exhausted, Pearson’s r = 0.766) and melanoma (Oliveira.TTE, Pearson’s r = 0.747) (table S5) (34, 36, 38, 39). These data suggest that the neoantigen-reactive CD4+ and CD8+ dysfunctional TIL states that we identified within colorectal cancer, breast cancer, and melanoma also exist in other tumor histologies. To investigate whether NeoTCR signatures can distinguish bystander viral-reactive TILs from tumor viral antigen–reactive TILs, we performed scRNA and TCR-seq on TILs from a lymph node metastasis from human papilloma virus 16 (HPV16)–positive anal squamous cell cancer (tumor 4397). From the tumor, there was one previously known CD8+ TCR reactive against HPV16 antigen E4 (the only HPV antigen expressed by the tumor; fig. S4, A to C). Despite being observed only once among the 941 sequenced T cells, when scored by scGSEA, the E4-reactive TCR (TCR1) was the fourthhighest NeoTCR8 signature–expressing cell (fig. S4D), which suggests that antitumor viral antigen–specific TILs are similar to neoantigenreactive dysfunctional TIL states, and that antitumor T cells in metastatic tumors may exist in shared dysfunctional states regardless of antigen class. We then tested the utility of NeoTCR signatures to prospectively predict antitumor neoantigen-reactive TILs from four independent tumor samples from patients with metastatic colon adenocarcinoma. We performed scRNA-seq and scTCR-seq on patient TILs from single-cell suspensions of surgically resected metastatic tumors and scored each individual T cell using NeoTCR8 and NeoTCR4 signatures to identify putative antitumor NeoTCR TIL states (fig. S5 and table S4). From 630 TILs sequenced from tumor 4393, we reconstructed eight candidate CD8+ TCRs and six candidate CD4+ TCRs using NeoTCR signatures and subsequently screened TCR-transduced T cells for their response to 156 autologous candidate

neoantigens, nine candidate tumor-associated antigens (table S11 and materials and methods), and a patient-derived xenograft (PDX) tumor line (Fig. 3, A to D, and fig. S6). The results of the screening assays indicated that four of the candidate CD8+ TCRs recognized a FAM63Amut (p.D460N) neoepitope and the autologous PDX, three CD8+ TCRs recognized the autologous PDX tumor but not any screened candidate neoantigens, one CD4+ TCR recognized a FUT1mut (p.343_344del) neoepitope, two CD4+ TCRs recognized a PCNTmut (p.P2122L) neoepitope, and one CD4+ TCR recognized the highly expressed nonmutated tumor-associated antigen (TAA) MAGEA6 (Fig. 3, B to D, and table S7). Backprojection of these 11 NeoTCRs indicated that they represented 29 single cells (or ~4.6%) of the single-cell map from tumor 4393 TILs (Fig. 3A). From tumor 4394, we synthesized and tested 12 CD8+ TCRs from the candidate CD8+ NeoTCR cluster against 185 autologous candidate neoantigens (Fig. 3E; no CD4+ clonotypes were tested because the CD4+ NeoTCR cluster comprised highly polyclonal singletons). We identified two CD8+ TCRs against the driver neoantigen KRASmut (p.G12V) and one CD8+ TCR that was nonreactive against screened mutations but did recognize an autologous PDX line (Fig. 3E and table S7). These three NeoTCRs represented 15 cells (0.5% of 2972 TILs) (Fig. 3E). From tumor 4400, we prospectively predicted 15 CD8+ TCRs and 14 CD4+ TCRs on the basis of NeoTCR4 and NeoTCR8 signatures (Fig. 3F). Neoantigen screening against 485 autologous candidate neoantigens and three highly expressed TAAs (table S11) led to the identification of five CD4+ TCRs that mediate recognition of KRASmut (p.G13D driver neoepitope) and nine CD8+ TCRs that were reactive with the tumor PDX line but did not recognize the screened neoantigen candidates (Fig. 3F and table S7). These 14 antitumor TCRs were expressed in 77 cells, representing 3.0% of the total cells

captured (Fig. 3F). From tumor 4421, we prospectively predicted 7 CD8+ TCRs and 11 CD4+ TCRs on the basis of candidate NeoTCR clusters and tested them against 239 autologous candidate neoantigens and an autologous tumor organoid (Fig. 3G and fig. S6). Two CD8+ TCRs recognized the ANO9mut p.151_154del neoepitope, one recognized the FLNBmut p.H2539Q neoepitope and organoid, and two recognized the UHRF2mut (p.R212P) neoepitope and organoid, whereas two CD8+ TCRs were exclusively organoid reactive (table S7). Two of the 11 CD4+ TCRs were also neoantigen reactive to ESRP1mut (p.E180D) and THOC6mut (p.R116H). These nine reactive TCRs represented 82 cells (0.8% of 10,049 TILs; Fig. 3G). From the four prospective patients, 37 of 73 (50.7%) predicted TCRs were reactive to tumors, neoantigens, or TAAs (Table 1). Among predicted CD8 TCRs, this frequency was 60.9%, and predicted CD4 TCRs were positive in our screen 35.4% of the time (Table 1). Notably, though our coculture assays of predicted CD4 TCRs did not show any direct antitumor reactivity, TCR recognition of tumor material through cross-presentation via antigen-presenting cells has not been evaluated. We did not identify any significant gene expression differences between TIL-expressing TCRs that were neoantigen and/or tumor reactive compared with TIL-containing TCRs that were nonreactive in our screens, nor did we find significant differences between gene expression profiles of neoantigen-specific TCRexpressing cells relative to exclusively PDX tumor–reactive TCR-containing cells that did not recognize screened candidate neoantigens (fig. S6). To assess the sensitivity and specificity of the NeoTCR signatures and compare them to other published T cell signatures in terms of their ability to successfully identify neoantigenreactive TCRs, we performed scGSEA on individual cells and performed ROC analysis of

Table 1. Summary of prospectively predicted TCRs from four patient tumor TILs to identify antitumor, neoantigen-reactive TCRs using the NeoTCR gene signature. “Tumor” refers to direct organoid or PDX reactivity. NeoAg, neoantigen; TAA, tumor-associated antigen. Prospective prediction of TCRs reactive with tumor CD8

CD4

Tumor and Tumor Tested NeoAg-reactive NeoAg only Tumor only Total Tested NeoAg-reactive TAA-reactive Tumor only

All Total

Tested Total

%

4393 8 4 0 3 7 6 3 1 0 4 14 11 79 ............................................................................................................................................................................................................................................................................................................................................ 4394 12 2 0 1 3 0 0 0 0 0 12 3 25 ............................................................................................................................................................................................................................................................................................................................................ 4400 15 0 0 9 9 14 5 0 0 5 29 14 48 ............................................................................................................................................................................................................................................................................................................................................ 4421 7 3 2 2 7 11 2 0 0 2 18 9 50 ............................................................................................................................................................................................................................................................................................................................................ All 42 9 2 15 26 31 10 1 0 11 73 37 50.7 61.9% 35.4% ............................................................................................................................................................................................................................................................................................................................................

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the ability of given signatures to call CD4+ NeoTCRs, CD8+ NeoTCRs, and public viral TCRs from the archival specimens (training sets; table S12 and fig. S7) and CD4+ NeoTCRs and CD8+ NeoTCRs from the prospective specimens (validation sets; Fig. 3H and table S12). In both the training and validation sets, the NeoTCR4 and NeoTCR8 signatures demonstrated the highest combination of sensitivity and specificity for CD4+ and CD8+ NeoTCRs, respectively (Fig. 3H, fig. S7, and table S12). We also identified TIL phenotypic states from other studies that performed well in our validation sets; namely, the bladder cancer–derived CD4.CXCL13 (31) and non–small cell lung cancer–derived CD4.Tfh.2 (39) signatures for CD4+ NeoTCRs, and terminally exhausted signatures from melanoma (38) and skin carcinoma (36) for CD8+ NeoTCRs. Although the studies did not examine the neoantigen reactivity of CD4+ T cells, the conserved phenotypic states shared with the validated CD4+ NeoTCRs identified here likely indicate that those samples also contain CD4+ neoantigenreactive T cells. Notably, signatures from stemlike T cells associated with ACT response (Krishna.ACT.StemLike) (45) and ICB response (CD8_G, Mem.Eff) (33) were especially poor at highlighting NeoTCRs, consistent with the majority of antitumor T cells being in a dysfunctional state in progressing metastatic cancer (Fig. 3H and table S12) (45). Finally, the relative median AUC values for the NeoTCR4 and NeoTCR8 signatures were low for public virus-reactive T cells, suggesting high specificity of this dysfunctional program for tumor antigen-specific TILs (table S12 and fig. S7). Combining scRNA data from all 15 sequenced tumors, we estimated that a median of 17.5 clonotypes will be present within a given CD8+ NeoTCR cluster, and 46.4 clonotypes will be present within a given CD4+ NeoTCR cluster for every 1000 TILs sequenced per patient (Fig. 3I), which markedly enhances the landscape of possible antitumor T cell clonotypes within solid tumors. In this Report, we have identified shared gene expression profiles of neoantigen-specific CD4+ and CD8+ T cells within metastatic solid human cancers. Neoantigen-specific TILs largely exhibited tumor-specific clonal expansion, with only limited overlap with dually expanded TILs found in the peripheral blood at the level of our sequencing depth (33, 34). Our results support prior high-dimensional phenotyping studies showing that tumor-reactive T cells are enriched within differentiated dysfunctional cellular states (23, 30, 31), with very few stemlike antitumor T cells (38, 45). We leveraged the NeoTCR dysfunctional signatures to identify antitumor TCRs with limited TIL material, in some cases identifying even an apparently unexpanded clonotype within the NeoTCR clusters as neoantigen reactive (e.g., tumor SCIENCE science.org

4323 TCR10). Using signatures derived from relatively few neoantigen-reactive clones (54 clonotypes expressed by 542 cells), more than half of all prospectively tested TCRs expressing NeoTCR4 or NeoTCR8 signatures in this analysis were neoantigen and/or tumor reactive, which suggests a high degree of tumor specificity in T cells that exhibit NeoTCR states. These signatures offer the potential to identify antitumor TCRs without the need for functional screening of candidate neoantigens. Further, as the roles of neoantigen-specific CD4+ T cells in establishing an antitumor response by supporting the activation of cytolytic CD8+ T cells have come into view (51, 52), the NeoTCR4 signature identified here will allow for expeditious identification of such CD4+ antitumor TCRs. Although the identified NeoTCR cells ranged from 0.1 to 9.1% of all TILs within the 14 tumors in which neoantigen reactivity was known, this likely represents an underestimate because we did not synthesize and experimentally determine tumor or mutation specificity for every TCR clonotype within the NeoTCR clusters, nor did we assess tumor or nonmutated TAA reactivity in the archival specimens (Fig. 3I). T cells expressing TCRs that target random mutations, mutations in tumor driver genes (e.g., KRAS, TP53, and PIK3CA), a nonmutated tumor-associated antigen (MAGEA6), an oncogenic viral antigen (HPV16-E4), and autologous tumor-reactive orphan receptors all converged on the same dysfunctional phenotype. Our results are further evidenced by a recent meta-analysis indicating that expression of CXCL13, one of the most differentially expressed genes within the NeoTCR4 and NeoTCR8 signatures, represents an independent variable for predicting responses to ICB (53). The existence of several orphan tumorreactive receptors that are reactive to autologous tumor material but tested negative against candidate neoantigens within the NeoTCR clusters also implies that the landscape of tumor antigens remains broader than that of the somatic mutations we have tested, as has been recently suggested (54–56). Further evidence for this point is the lack of gene expression differences between NeoTCR signature–expressing cells that tested negative in our screens and those that tested positive. We find it likely that intratumoral T cells that acquire a dysfunctional, clonally expanded phenotype do so because they are reacting to tumor-relevant antigens, although this study did not investigate whether differences in target antigen expression or TCR functional avidity can differentially contribute to T cell dysfunction. We propose that TCRs from cells in the NeoTCR transcriptomic state can be rapidly identified without additional TIL growth, activation, or testing, thus providing opportunities to develop patient-specific neoantigen-

targeting TCR immunotherapies against metastatic solid tumors, even when endogenous NeoTCR-expressing cells from those tumors are dysfunctional and/or exhausted. The potential roles of the genes expressed in the NeoTCR signature (including those that have unknown T cell function) in mediating tumor-specific TIL dysfunction in metastatic human cancers also remain to be explored in future studies. REFERENCES AND NOTES

1. P. F. Robbins et al., J. Clin. Oncol. 29, 917–924 (2011). 2. R. A. Morgan et al., Science 314, 126–129 (2006). 3. C. H. June, M. Sadelain, N. Engl. J. Med. 379, 64–73 (2018). 4. J. N. Kochenderfer, Z. Yu, D. Frasheri, N. P. Restifo, S. A. Rosenberg, Blood 116, 3875–3886 (2010). 5. R. L. Siegel, K. D. Miller, A. Jemal, CA Cancer J. Clin. 70, 7–30 (2020). 6. R. A. Morgan et al., Mol. Ther. 18, 843–851 (2010). 7. M. R. Parkhurst et al., Mol. Ther. 19, 620–626 (2011). 8. G. P. Linette et al., Blood 122, 863–871 (2013). 9. E. Tran, P. F. Robbins, S. A. Rosenberg, Nat. Immunol. 18, 255–262 (2017). 10. P. F. Robbins et al., Nat. Med. 19, 747–752 (2013). 11. M. R. Parkhurst et al., Cancer Discov. 9, 1022–1035 (2019). 12. M. M. Gubin et al., Nature 515, 577–581 (2014). 13. N. van Rooij et al., J. Clin. Oncol. 31, e439–e442 (2013). 14. M. Parkhurst et al., Clin. Cancer Res. 23, 2491–2505 (2017). 15. D. B. Keskin et al., Nature 565, 234–239 (2019). 16. J. D. Altman et al., Science 274, 94–96 (1996). 17. A. Han, J. Glanville, L. Hansmann, M. M. Davis, Nat. Biotechnol. 32, 684–692 (2014). 18. Y.-C. Lu et al., Mol. Ther. 26, 379–389 (2018). 19. C. U. Blank et al., Nat. Rev. Immunol. 19, 665–674 (2019). 20. A. M. van der Leun, D. S. Thommen, T. N. Schumacher, Nat. Rev. Cancer 20, 218–232 (2020). 21. T. Duhen et al., Nat. Commun. 9, 2724 (2018). 22. A. Gros et al., J. Clin. Invest. 124, 2246–2259 (2014). 23. Y. Simoni et al., Nature 557, 575–579 (2018). 24. R. Yossef et al., JCI Insight 3, e122467 (2018). 25. W. Scheper et al., Nat. Med. 25, 89–94 (2019). 26. A. Pasetto et al., Cancer Immunol. Res. 4, 734–743 (2016). 27. E. J. Wherry et al., Immunity 27, 670–684 (2007). 28. D. R. Sen et al., Science 354, 1165–1169 (2016). 29. A. C. Scott et al., Nature 571, 270–274 (2019). 30. H. Li et al., Cell 181, 747 (2020). 31. D. Y. Oh et al., Cell 181, 1612–1625.e13 (2020). 32. C. S. Jansen et al., Nature 576, 465–470 (2019). 33. M. Sade-Feldman et al., Cell 176, 404 (2019). 34. T. D. Wu et al., Nature 579, 274–278 (2020). 35. B. C. Miller et al., Nat. Immunol. 20, 326–336 (2019). 36. K. E. Yost et al., Nat. Med. 25, 1251–1259 (2019). 37. I. Tirosh et al., Science 352, 189–196 (2016). 38. G. Oliveira et al., Nature 596, 119–125 (2021). 39. J. X. Caushi et al., Nature 596, 126–132 (2021). 40. S. Valpione et al., Nat. Commun. 12, 4098 (2021). 41. D. V. Bagaev et al., Nucleic Acids Res. 48, D1057–D1062 (2020). 42. N. Levin et al., Clin. Cancer Res. 27, 5084–5095 (2021). 43. Y.-C. Lu et al., J. Immunother. Cancer 9, e002595 (2021). 44. B. C. Paria et al., J. Immunother. 44, 1–8 (2021). 45. S. Krishna et al., Science 370, 1328–1334 (2020). 46. E. Ghorani et al., Nat. Cancer 1, 546–561 (2020). 47. C. Gu-Trantien et al., JCI Insight 2, 91487 (2017). 48. A. E. Denton et al., J. Exp. Med. 216, 621–637 (2019). 49. R. Cabrita et al., Nature 577, 561–565 (2020). 50. N. S. Joshi et al., Immunity 43, 579–590 (2015). 51. E. Alspach et al., Nature 574, 696–701 (2019). 52. C. Cui et al., Cell 184, 6101–6118.e13 (2021). 53. K. Litchfield et al., Cell 184, 596–614.e14 (2021). 54. W. Yang et al., Nat. Med. 25, 767–775 (2019). 55. V. Roudko et al., Cell 183, 1634–1649.e17 (2020). 56. M. H. Gee et al., Cell 172, 549–563.e16 (2018). AC KNOWLED GME NTS

We thank the Surgery Branch TIL Laboratory and clinical team for generating TIL; we also thank patients enrolled in our clinical protocols. This work utilized the computational resources of the

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NIH HPC Biowulf cluster (http://hpc.nih.gov). We also thank NIDAP for providing additional computational support and the CCR Genomics Core for next-generation sequencing support. Funding: This research was supported by the Center for Cancer Research intramural research program of the National Cancer Institute. Support from the CCR Single Cell Analysis Facility was funded by FNLCR contract no. HHSN261200800001E. This project has been funded in part with federal funds from the National Cancer Institute, National Institutes of Health, under contract no. 75N91019D00024. The content of this publication does not necessarily reflect the views or policies of the Department of Health and Human Services, nor does mention of trade names, commercial products, or organizations imply endorsement by the US government. Author contributions: F.J.L., S.Kr., P.F.R., and S.A.R. conceived the study and designed experiments; F.J.L., S.Kr., N.B.P., and S.L.G. curated patient samples for inclusion; F.J.L.,

S.Kr., R.Y., N.B.P., P.D.C., N.Z., N.L., M.R.P., Z.Y., N.R.V., K.J.H., Y.C.L., Z.Z., L.J., J.J.G., S.S., V.K.H., A.R.C., A.S., R.V.M., B.G., S.Ki., S.K.N., B.C.P., Y.F.L., M.F., L.T.N., S.R., M.L.S., S.T.L., R.S., C.T., A.P., T.D.P., R.B., and M.C.K. performed experiments; F.J.L., S.Kr., R.Y., S.S., N.B.P., K.H., J.C.Y., and P.D.C. performed data analysis; and F.J.L., S.Kr., and S.A.R. wrote the manuscript, with input from all authors. Competing interests: F.J.L., S.Kr., R.Y., K.H., J.C.Y., P.F.R., and S.A.R. are listed as inventors on a patent application (US provisional patent application no. 62/992,701, PCT patent application no. PCT/US2021/023240) submitted by NCI that covers the use of NeoTCR signatures to identify antitumor TCRs. The other authors declare no competing interests. Data and materials availability: All data are available in the main text or the supplementary materials. Sequencing data generated as part of this study are available on dbGaP (the Database of Genotypes and Phenotypes) under accession no. phs002748.v1.p1. Previously published tumor

OPTICS

Topological modes in a laser cavity through exceptional state transfer A. Schumer1,2, Y. G. N. Liu1, J. Leshin3, L. Ding1, Y. Alahmadi3,4, A. U. Hassan3, H. Nasari1,3, S. Rotter2, D. N. Christodoulides3, P. LiKamWa3, M. Khajavikhan1* Shaping the light emission characteristics of laser systems is of great importance in various areas of science and technology. In a typical lasing arrangement, the transverse spatial profile of a laser mode tends to remain self-similar throughout the entire cavity. Going beyond this paradigm, we demonstrate here how to shape a spatially evolving mode such that it faithfully settles into a pair of bi-orthogonal states at the two opposing facets of a laser cavity. This was achieved by purposely designing a structure that allows the lasing mode to encircle a non-Hermitian exceptional point while deliberately avoiding non-adiabatic jumps. The resulting state transfer reflects the unique topology of the associated Riemann surfaces associated with this singularity. Our approach provides a route to developing versatile mode-selective active devices and sheds light on the interesting topological features of exceptional points.

T

he quantum adiabatic theorem, a corollary of the Schrödinger equation, provides excellent insights into the behavior of slowly varying quantum systems. When the Hamiltonian gradually changes in time, the associated probability densities tend to evolve smoothly, thus allowing a quantum system to remain in its initial eigenstate. If this evolution follows a cyclic path around a spectral degeneracy, then the related eigenvalue can acquire a geometric phase that solely depends on the traversed trajectory in parameter space (1, 2). In condensed-matter physics, when dealing with momentum space, it can be shown that the related concepts of Berry connection and curvature, which lift the path dependency of the observables, give

1

Ming Hsieh Department of Electrical and Computer Engineering, University of Southern California, Los Angeles, CA 90089, USA. 2Institute for Theoretical Physics, Vienna University of Technology (TU Wien), A-1040 Vienna, Austria. 3 CREOL, The College of Optics and Photonics, University of Central Florida, Orlando, FL 32816, USA. 4Center of Excellence for Telecomm Applications, Joint Centers of Excellence Program, King Abdul Aziz City for Science and Technology, Riyadh 11442, Saudi Arabia. *Corresponding author. Email: [email protected]

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rise to a host of fundamental topological properties such as nonzero Chern number and integer quantum Hall conductance in solids (3). Non-Hermitian systems and their spectral degeneracies, better known as exceptional points (EPs), have attracted attention in various physical disciplines ranging from optics to electronics, optomechanics, and acoustics (4–14). An interesting feature of these non-Hermitian systems is that, under the appropriate conditions, their eigenvalues and corresponding eigenvectors tend to simultaneously coalesce, forming spectral degeneracies known as EPs (4, 15). The presence of EPs not only affects a configuration that is statically operating in their vicinity but also alters the dynamical response of non-Hermitian systems. In contrast to a quasistatic encirclement of a Hermitian degeneracy (Fig. 1C), cyclic parameter variations in non-Hermitian systems do not necessarily reproduce the input state (apart from a geometric phase) after completing a loop around an EP. Instead, a quasistatic cycle leads to a swap of the instantaneous eigenstates (Fig. 1D) (3, 8, 9, 16, 17). Even more interesting is

exome and RNA-seq data can be found on dbGaP under accession nos. phs002735.v1.p1 and phs001003.v2.p1, respectively. SUPPLEMENTARY MATERIALS

science.org/doi/10.1126/science.abl5447 Materials and Methods Figs. S1 to S7 Tables S1 to S12 References (57Ð69) MDAR Reproducibility Checklist

22 July 2021; accepted 20 January 2022 Published online 3 February 2022 10.1126/science.abl5447

the behavior of a non-Hermitian system when the EP encirclement is carried out dynamically. In this latter case, the complex nature of the eigenvalues inhibits adiabatic evolution for all eigenvectors except for the one with the largest imaginary part of the corresponding eigenvalue due to non-adiabatic jumps (17–19). Instead, these jumps produce a chiral behavior unique to non-Hermitian systems, in which the final state after a dynamic loop around an EP depends on the loop’s winding direction rather than on the initial state at the loop’s outset (Fig. 1F) (9, 19–25). Although this chiral behavior has recently been observed in a number of physical systems (9, 20–22, 24, 26), little has been done to exploit this concept to establish a purely topological state in non-Hermitian configurations (27–29). We introduce a type of topological mode appearing in non-Hermitian cavities that feature dynamical EP encirclement. In these systems, the interplay among the Riemann surfaces, the net gain, and gain saturation favors a spatially evolving lasing mode that morphs from one eigenstate profile to another while avoiding the aforementioned nonadiabatic jumps. As a result, we demonstrate a topologically operating single transverse mode laser that is capable of simultaneously emitting in two different, but topologically linked, transverse profiles, each from a different facet. Apart from its counterintuitive behavior, this laser constitutes an adiabatic non-Hermitian cavity that supports a fully topological resonant mode. The implementation of EP encircling with gain additionally avoids the considerable absorption losses that plagued previous reports of chiral state transfer with dissipative elements (9, 20–22, 24, 26). Furthermore, because the topological energy transfer relies solely on the adiabatic encircling of an EP degeneracy and not on the exact shape of the loop, the resulting lasing mode is robust against defects and fabrication imperfections, as well as fluctuations in gain [see the materials and methods (30), sections 5 and 6]. science.org SCIENCE

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Fig. 1. Encircling a Hermitian or a non-Hermitian degeneracy. Occurrence of the interchange of the instantaneous eigenvectors when cycling around a degeneracy along a closed loop C is independent of its shape and only depends on the type of the enclosed degeneracy. (A and B) Energy surfaces of a Hermitian (top) and of a non-Hermitian degeneracy (bottom). The colors in (B), (D), and (F) are connected to the imaginary part of the eigenvalues indicating the gain [ℑðlÞ > 0; red] and loss [ℑðlÞ < 0; blue] behavior of the respective eigenvectors. (C to F) Topological equivalent of winding around a degeneracy. A cycle around a Hermitian degeneracy is represented by an untwisted closed sheet, and a loop enclosing a non-Hermitian degeneracy corresponds to a Möbius strip. The     eigenvector population pðzÞ ¼ jcþ ðzÞj2 jc ðzÞj2 = jcþ ðzÞj2 þ jc ðzÞj2 ;

Our laser cavity consists of two transversely coupled waveguides in a parity-time (PT) symmetric configuration, in which one of the elements is subject to gain whereas the other one experiences loss (or a lower level of gain). A schematic of the device is shown in Fig. 2B, and SEM images are shown in the insets of Fig. 2C. The dynamical encircling of the induced EP in time is implemented by modulating certain parameters of the structure along the propagation direction, z. Specifically, by varying the coupling and the detuning between the two singlemode waveguides in a continuous fashion, the system’s transverse modes are steered around the EP as light circulates in the cavity. Each waveguide is accompanied by a neighboring strip that induces a change in its effective refractive index, providing the required detuning. These loading strips are intentionally designed not to be phase matched to the waveguide elements. The detuning between the two waveguides is thus determined by the distance between each waveguide and its adjacent strip and varies according to s(z) = s0 + (smin – s0 )sin(2pz/L) [see the SCIENCE science.org

where YðzÞ ¼ cþ ðzÞFþ ðzÞ þ c ðzÞF ðzÞ, is displayed on the vertical axis, such that the two instantaneous eigenstates F±(z) lie on the edges of the sheets. (C) Quasistatically winding around a Hermitian degeneracy along C returns each eigenvector to itself. (E) Adiabatic cycling a Hermitian degeneracy starting from an eigenstate, e.g., Y(0) = F– (0) (orange arrow), yields the same eigenvector after traversing C, i.e., Y(L) ≈ F– (0). (D) Quasistatic evolution around an EP corresponds to the topology of a Möbius strip as the eigenvectors interchange [F±(0) º F∓(L)]. (F) Upon dynamic EP encircling in the CW direction, any initial excitation [orange sphere: Y(0) = F–(0); purple sphere: Y(0) = F+(0)] is transferred toward F–, such that after one cycle the state vector yields Y(L) ≈ F–(L) º F+(0) (left panel). When looping in CCW direction, every initial state is again drawn to F–, but the state vector then gives Y(L) ≈ F–(0) (right panel), leading to a chiral state transfer.

materials and methods (30), section 1]. Conversely, the dynamic coupling is attained by modulating the separation between the two primary waveguides, i.e., d(z) = d0 + (dmax – d 0 )sin(pz/L). Using the aforementioned modulation patterns, an EP-encircling loop is realized in parameter space when the light travels through the cavity once (half a cavity roundtrip), as shown in Fig. 2, A and B. The propagation direction of the wave through the cavity then determines the directionality of the EP encircling. During a full cavity roundtrip, the EP is therefore encircled twice, once in each direction. The two loops of opposing directions in parameter space are chosen in such a way that non-adiabatic jumps are avoided (orange/ purple line in left/right panel of Fig. 1F). It is this back and forth in the cavity that allows a single topological mode to be formed that is independent of the path taken in parameter space. When a PT-symmetric pump profile is applied, in the absence of nonlinearities and saturation, the transverse mode evolution in the above active system is governed by a

Schrödinger-type equation i@ zY(z) = H(z)Y(z) with Y(z) = [E1(z), E2(z)]T, where the z-dependent Hamiltonian is given by  H ðz Þ ¼

dðz Þ ig þ ig k ðz Þ

k ðz Þ dðz Þ ig

 ð1Þ

where d(z) is the detuning, k(z) is the coupling, g is the linear absorption loss, and g is the gain provided through pumping. The instantaneous eigenvalues and eigenvectors of the Hamiltonian can be expressed as l±(z) = i(g/2 – g) ± k(z)cos[q(z)] and F±(z) = {2cos[q(z)]}–1/2 (e±iq(z)/2, ±e∓iq(z)/2)T, respectiveh i ðz Þ ly, where qðz Þ ¼ arcsin g=2þid ∈ ℂ. The PTkðz Þ symmetry line is situated along d = 0, with the EP located at kEP = g/2 separating the PT-broken (g/2 > k) from the PT-symmetric (g/2 < k) phase. The start/end point of the EPencircling section is at d = 0 and k » g/2, and is chosen such that q(0) = q0 ≈ g/2k « 1. Consequently, the eigenvector components are approximately equal in magnitude, which implies 25 FEBRUARY 2022 • VOL 375 ISSUE 6583

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Fig. 2. Operation principle and laser structure. (A) Parameter path encircling the EP in the plane spanned by the normalized coupling ~k and detuning ~d. (B) Illustration of the EP-encircling laser (not to scale). In addition to the losses caused by absorption in both waveguides, the red waveguide experiences gain by optically pumping the encircling section of the cavity. The separation between the detuners and their respective main waveguides introduces detuning d(z), whereas the separation between the two main waveguides generates coupling k(z). The grating reflector on the left end of each main waveguide acts as a wavelength filter. The steady-state topological mode is characterized by the simultaneous emission of the in-phase (right end) and p-out-of-phase (left end) mode, each from one facet. (C) SEM images (small panels) of the laser structure demonstrating the variation of the separations between detuners as well as the main waveguides.

Fig. 3. Numerically simulated transient and steady-state behavior of the encircling part of the cavity. (A and B) Numerical simulations of the transient field evolution for six passes in alternating directions through the cavity in the presence of gain saturation. In total, 100 individual solutions of Equations 2a and 2b based on purely stochastic excitations are shown as thin green (A) and red (B) lines. The thick gray lines show the instantaneous eigenstate F–(z) without noise. (A) The relative phase between the two waveguides evolves continuously from –p to 0 and back within one round trip. (B) After an initial population transfer toward F–, the normalized eigenvector population p shows that the ensuing adiabatic following of said eigenstate leads to the emission of different supermodes from each facet. (C and D) Evolution of the relative phase between the two cavities and the normalized intensity difference, respectively, of the left-to-right (purple) and right-to-left (cyan) traveling waves according to a Rigrod-type self-consistent

that the two supermodes emit with equal intensity in both waveguides at either facet. At z = 0, the relative phase ϕ between the waveguide amplitudes of the supermodes is approximately ϕ–(0) ≈ –p (p-out-of-phase) and ϕ+(0) ≈ 0 886

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simulation using Equations 3a and 3b. Emissions of different supermodes from each facet are shown. The two spatial supermodes are characterized by equal intensity in both waveguides at the output ports and a phase difference that evolves from –p to 0 and back.

(in-phase) for F– and F+, respectively. This is exactly reversed at the end of the encircling section (z = L), i.e., ϕ–(L) ≈ 0 and ϕ+(L) ≈ –p, such that the adiabatic following along the topological mode F–(z) continuously morphs

the transverse mode profile from being p-outof-phase at one end to being in-phase at the opposite end of the cavity [for details, see the materials and methods (30), sections 5 and 6]. science.org SCIENCE

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Fig. 4. Near- and far-field intensity profiles, light-light curves, and spectra. (A to C) Experimental and simulation results, respectively, of the CW encircling scheme resulting in the in-phase supermode with a single bright central lobe. (D to F) Encircling the EP in the CCW direction results in the emission of the p-out-of-phase supermode, which has a central dark spot between two bright lobes. (A) and (D) show the respective near-field intensity profiles. Experimental far-field intensity distributions in (B) and (E) are colorized for a clearer visual characterization. (C) and (F) show the simulated far-field intensity pattern. (G) Normalized Light-light curves of the CW and CCW encirclement state showing a characteristic lasing threshold. (H) Spectra of the CW and CCW encirclement setting.

To intuitively understand the topological nature of this process, one may consider a random superposition of the transverse eigenvectors that are excited at one end of the encircling section of the device after establishing the desired PT-symmetric pump profile. Irrespective of the initial excitation, by the end of a roundtrip in the cavity, the state vector has undergone (at most) a single non-adiabatic transition toward the eigenvector subject to gain (purple/orange line in left/right panel of Fig. 1F) and is then caught in the adiabatic (fully topological) cycle, traveling back and forth between the facets. In fact, additional non-adiabatic transitions are forbidden because F– is the amplified supermode throughout the entire length of the cavity. This transient behavior is simulated using the following nonlinear coupled stochastic differential equations, when excited through h2 j white noise j~ h1 j»j~ dE1 ð~z Þ g~1 E1 ð~z Þ ¼ d~z 1 þ jE1 ð~z Þ=Es j2 i~dð~z ÞE1 ð~z Þ

~gE1 ð~z Þ þ

i~ kð~z ÞE2 ð~z Þ þ ~ h1 ð~z Þ

SCIENCE science.org

(2a)

dE2 ð~z Þ ¼ d~z

~gE2 ð~z Þ

i~dð~z ÞE2 ð~z Þ

h2 ð~z Þ i~ kð~z ÞE1 ð~z Þ þ ~

(2b)

where E1 ð~z Þ and E2 ð~z Þ are the field amplitude in the waveguide subject to gain and loss, respectively, and Es is the saturation field. All of the parameters are normalized with respect to the maximum coupling k0 = k(0) = k(L), i.e., ~g ¼ g=k0 , ~d ¼ d=k0 , g~1 ¼ g1 =k0 , ~ ¼ k=k0 , and ~z ¼ k0 z . After each passage k through the cavity, the field amplitudes are reflected by the facets and travel through the system in the opposite direction. The backand-forth propagation of 100 individual solutions to Equations 2a and 2b for a total of six cycles is shown in Fig. 3, A and B. We observed that any initial excitation was transferred toward the instantaneous eigenstate F– within one cycle, and the ensuing propagation follows this eigenvector adiabatically as the EP is repeatedly encircled in opposite direction. The relative phase between the waveguide amplitudes changes continuously from –p to 0 and back during a full roundtrip.

Finally, to obtain a self-consistent steady state lasing solution, a Rigrod-type model was used that considers the waves in both cavities traveling left to right and right to left simultaneously (31) 2 g~1 E1T ð~z Þ dE1T ð~z Þ   ¼ T4 2 d~z 1 þ jE1þ ð~z Þ=Es j þ jE1 ð~z Þ=Es j2

#

~gE1T ð~z Þ

þ

i~dð~z ÞE1T ð~z Þ

i~ kð~z ÞE2T ð~z Þ

dE2T ð~z Þ ¼ T½ ~gE2T ð~z Þ i~dð~z ÞE2T ð~z Þ d~z i~ kð~z ÞE1T ð~z ފ

(3a)

(3b)

Here, the subscripts 1 and 2 refer to the first and second waveguide, respectively, and the superscripts correspond to the wave propagating from left to right (+) and right to left (–). The lasing modes have to replicate after each roundtrip within the resonator and obey the boundary conditions Eiþ ð0Þ ¼ RL Ei ð0Þ and Ei ðk0 LÞ ¼ RR Eiþ ðk0 LÞ, where RL and RR are the reflectances at the left and right facet, respectively. After the transient behavior has settled in the instantaneous eigenvector F–, the dynamical encircling process is characterized solely by the topological adiabatic energy 25 FEBRUARY 2022 • VOL 375 ISSUE 6583

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transfer between the two mode profiles at the output ports. The ratios of the field intensities in the two waveguides are equal at each facet (Fig. 3D), whereas the relative phase of the state vector changes from ϕ ≈ –p at z = 0 to ϕ ≈ 0 at z = L (Fig. 3C), corroborating that the system is lasing in the topological mode F– [also see the materials and methods (30), section 9]. The laser structures are fabricated on an InP substrate wafer containing a 300-nm InGaAsP multiple quantum well active region that is covered with 500 nm of an epitaxially grown InP layer. The fabrication procedure for realizing the devices is described in the materials and methods (30), section 2. The structure comprises a 2-mm-long encircling path, after which the two loaded-strip waveguides are separated further to prevent additional coupling. In the main part, the width of each waveguide is 900 nm, and the separation between the two waveguides varies between 600 and 1500 nm. The width of the detuning strips is 400 nm, and their distance to the waveguides changes between 300 and 900 nm. The electromagnetic simulations of the modes, coupling strengths, and detunings can be found in the materials and methods (30), section 1. Because of the short free spectral range of the cavities, 2-mm-long grating mirrors based on sidewall modulation are incorporated at one end of the two waveguides to limit the number of longitudinal modes (Fig. 2, B and C). The gratings are identical (ridge widths: 1200 nm; period: 246 nm; duty cycle: 50%) and designed to promote spectrally narrow emission at ~1596 nm [see the materials and methods (30), section 3]. The fabricated laser structure is pumped with a 1064-nm pulsed beam, focused by a highmagnification near-infrared (NIR) objective and cylindrical lenses positioned before the sample. This produces a pump beam with a width of 8 mm and a length of 2 mm. By adjusting the position of the beam with respect to the pattern, one waveguide can be pumped with almost constant intensity over the entire length of the device, whereas the other is left with little to no pump energy. A PT-symmetric configuration is thus established, exhibiting an EP at the gain contrast value g1/2 = k. The level of gain contrast can be selected by changing the position of the pump beam. The in-plane emission from the edge facet of the laser is collected and imaged on a NIR camera and a spectrometer for further analysis. By changing the location of the waveguide facets with respect to the objective lens, one can maneuver between observing the near- and far-field intensity patterns in the camera. The details of the measurement station are described in the materials and methods (30), section 4. 888

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To factor out the effect of the dissimilarities between the two ends of the structure, we alternately pump either the first or the second waveguide and collect the emission from the same facet. Changing the pump profile switches the order of clockwise (CW) and counterclockwise (CCW) encirclements in a roundtrip, thus enabling us to observe the cavity output from the two ends without requiring us to switch the probed facet. After the encircling section, the two waveguides are gradually separated to a distance of 5 mm at the emitting end, thus allowing the observation of both near-field and far-field through our configuration. Here, when the upper waveguide is pumped, the left-to-right propagating wave corresponds to dynamically encircling the EP in CW direction, leading to an in-phase emission profile at the designated facet, followed by a CCW winding that promotes the p-out-ofphase-mode on the other facet. This difference is particularly evident in the far-field intensity distribution, which shows a bright lobe in the center of the interference pattern for the inphase mode (Fig. 4, A to C) when the first waveguide is pumped. By shifting the position of the pump light to the second waveguide, the EP-encircling direction is reversed, resulting in a situation equivalent to viewing the opposite facet. In this case, the p-out-of-phase supermode leads to a far-field pattern with a node at the center and two bright lobes around it (Fig. 4, D to F). In both cases, the near-field intensity patterns are similar (Fig. 4, A and D), with the two waveguides emitting with nearly equal intensity (the slight difference is caused by the unequally pumped separated regions). Together with the far-field profile, this confirms that the observed patterns belong to the desired in-phase and p-outof-phase emission profiles of the corresponding topological mode [also see the materials and methods (30), section 10]. Finally, to verify that the structure is indeed lasing, the lightlight curves are collected for both pump scenarios (Fig. 4G). The lasing spectra for both outputs are shown in Fig. 4H, with their peak wavelength occurring near 1596 nm. Unlike standard coupled waveguide lasers, which tend to show frequency splitting, here, the conversion from one state to the other along the cavity results in the same phase accumulation and resonance wavelength for both output states. Our device presents a demonstration of lasing through topological mode transfer. These lasing structures exhibit emission profiles that are robust to various parameter variations that tend to cause instabilities and temporal fluctuations in standard lasers. Extending this concept to larger arrays can result in laser systems with fast switching between various spatial supermodes by appropriately modulating the pump profile. Our work also

provides a route to the study of topological effects in non-Hermitian systems by linking the elimination of non-adiabatic jumps to the formation of spatially evolving topological modes in laser cavities. REFERENCES AND NOTES

1. S. Pancharatnam, Proc. Indian Acad. Sci. Sect. A Phys. Sci. 44, 247–262 (1956). 2. M. V. Berry, Proc. R. Soc. A Math. Phys. Eng. Sci. 392, 45–57 (1984). 3. C. Dembowski et al., Phys. Rev. Lett. 86, 787–790 (2001). 4. W. D. Heiss, J. Phys. A: Math. Gen. 37, 2455–2464 (2004). 5. M. P. Hokmabadi, A. Schumer, D. N. Christodoulides, M. Khajavikhan, Nature 576, 70–74 (2019). 6. H. Jing et al., Sci. Rep. 5, 9663 (2015). 7. H. Hodaei et al., Nature 548, 187–191 (2017). 8. A. Bergman et al., Nat. Commun. 12, 486 (2021). 9. J. Feilhauer et al., Phys. Rev. A 102, 040201 (2020). 10. H. Hodaei, M. A. Miri, M. Heinrich, D. N. Christodoulides, M. Khajavikhan, Science 346, 975–978 (2014). 11. B. Peng et al., Science 346, 328–332 (2014). 12. M. Brandstetter et al., Nat. Commun. 5, 4034 (2014). 13. Z. Lin et al., Phys. Rev. Lett. 106, 213901 (2011). 14. A. Regensburger et al., Nature 488, 167–171 (2012). 15. T. Kato, Perturbation Theory for Linear Operators (Springer, ed. 2, 1995), vol. 132 of Classics in Mathematics. 16. C. Dembowski et al., Phys. Rev. E 69, 056216 (2004). 17. R. Uzdin, A. Mailybaev, N. Moiseyev, J. Phys. A: Math. Theor. 44, 435302 (2011). 18. T. J. Milburn et al., Phys. Rev. A 92, 052124 (2015). 19. I. Gilary, A. A. Mailybaev, N. Moiseyev, Phys. Rev. A 88, 010102 (2013). 20. J. Doppler et al., Nature 537, 76–79 (2016). 21. H. Xu, D. Mason, L. Jiang, J. G. E. Harris, Nature 537, 80–83 (2016). 22. J. W. Yoon et al., Nature 562, 86–90 (2018). 23. X.-L. Zhang, S. Wang, B. Hou, C. T. Chan, Phys. Rev. X 8, 021066 (2018). 24. X.-L. Zhang, T. Jiang, C. T. Chan, Light Sci. Appl. 8, 88 (2019). 25. A. U. Hassan, B. Zhen, M. Soljačić, M. Khajavikhan, D. N. Christodoulides, Phys. Rev. Lett. 118, 093002 (2017). 26. J. B. Khurgin et al., Optica 8, 563–569 (2021). 27. L. J. Maczewsky et al., Science 370, 701–704 (2020). 28. K. Wang et al., Science 371, 1240–1245 (2021). 29. S. Xia et al., Science 372, 72–76 (2021). 30. Materials and methods are available as supplementary materials. 31. G. R. Hadley, J. Appl. Phys. 58, 97–100 (1985). AC KNOWLED GME NTS

Funding: This work was supported by DARPA (grant D18AP00058), the Office of Naval Research (grants N00014-16-1-2640, N00014-18-1-2347, N00014-19-1-2052, N00014-20-1-2522, and N00014-20-1-2789), the Army Research Office (grant W911NF-17-10481), the National Science Foundation (grants ECCS 1454531, DMR 1420620, ECCS 1757025, CBET 1805200, ECCS 2000538, and ECCS 2011171), the Air Force Office of Scientific Research (grants FA9550-14-1-0037, FA9550-20-1-0322, and FA9550-21-1-0202), the US–Israel Binational Science Foundation (BSF grant 2016381), the Jet Propulsion Laboratory (grant 013385-00001), the European Commission project NHQWAVE (grant MSCA-RISE 691209), and the Austrian Science Fund (FWF) project WAVELAND (grant P32300). Author contributions: M.K., D.N.C., S.R., and P.L. conceived the project. A.S., Y.G.N.L., J.L., L.D., Y.A., A.U.H., and H.N. conducted the theoretical and experimental investigations. All authors contributed to the preparation of the manuscript. Competing interests: The authors declare no competing interests. Data and materials availability: All data are available in the main text or the supplementary materials. SUPPLEMENTARY MATERIALS

science.org/doi/10.1126/science.abl571 Materials and Methods Supplementary Text Fig S1 to S13 References (32–36) 28 July 2021; accepted 25 January 2022 10.1126/science.abl6571

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ANTIBIOTIC RESISTANCE

Minimizing treatment-induced emergence of antibiotic resistance in bacterial infections Mathew Stracy1,2, Olga Snitser1, Idan Yelin1, Yara Amer1, Miriam Parizade3, Rachel Katz3, Galit Rimler3, Tamar Wolf3, Esma Herzel4, Gideon Koren4, Jacob Kuint4,5, Betsy Foxman6, Gabriel Chodick4,5, Varda Shalev4,5, Roy Kishony1,7,8* Treatment of bacterial infections currently focuses on choosing an antibiotic that matches a pathogen’s susceptibility, with less attention paid to the risk that even susceptibility-matched treatments can fail as a result of resistance emerging in response to treatment. Combining whole-genome sequencing of 1113 pre- and posttreatment bacterial isolates with machine-learning analysis of 140,349 urinary tract infections and 7365 wound infections, we found that treatment-induced emergence of resistance could be predicted and minimized at the individual-patient level. Emergence of resistance was common and driven not by de novo resistance evolution but by rapid reinfection with a different strain resistant to the prescribed antibiotic. As most infections are seeded from a patient’s own microbiota, these resistance-gaining recurrences can be predicted using the patient’s past infection history and minimized by machine learning–personalized antibiotic recommendations, offering a means to reduce the emergence and spread of resistant pathogens.

U

rinary tract infections (UTIs) and wound infections are two of the most common conditions for which antibiotics are prescribed (1–3). These infections are frequently seeded from bacteria from a patient’s own microbiota; uropathogens can persist for years in a patient’s gut microbiota, which often acts as a reservoir for future infections (4–6). Wound infections are commonly caused by pathogens from a patient’s skin microbiota, as well as pathogens from the gut flora (7). Both UTIs and wound infections can be treated by a range of antibiotics, but resistance is widespread among the causative pathogens, and considerable efforts are being made to develop strategies to minimize susceptibility mismatches, where an antibiotic is mistakenly prescribed to treat an infection resistant to it (8–10). Yet even when an antibiotic is correctly prescribed to treat a pathogen sensitive to it (i.e., susceptibility-matched), treatment is a double-edged sword: It may clear the ongoing infection, but it may also select for resistant pathogens among a patient’s resident microbial population, limiting current and future treatment efficacy (11, 12). Indeed, prior antibiotic use is a strong risk factor for resistant UTIs and wound infections at the individualpatient level (8, 13–19). This is especially 1 Faculty of Biology, Technion–Israel Institute of Technology, Haifa, Israel. 2Department of Biochemistry, University of Oxford, Oxford, UK. 3Maccabi Mega Lab, Maccabi Healthcare Services, Tel Aviv, Israel. 4 Maccabitech, Maccabi Healthcare Services, Tel Aviv, Israel. 5Sackler Faculty of Medicine, Tel Aviv University, Tel Aviv, Israel. 6Department of Epidemiology, University of Michigan School of Public Health, Ann Arbor, MI, USA. 7 Department of Computer Science, Technion–Israel Institute of Technology, Haifa, Israel. 8Lorry I. Lokey Interdisciplinary Center for Life Sciences and Engineering, Technion–Israel Institute of Technology, Haifa, Israel.

*Corresponding author. Email: [email protected]

SCIENCE science.org

problematic because these infections are often recurrent or chronic, with patients receiving multiple courses of antibiotics (3, 4, 20, 21). Despite the importance of the emergence of resistance during or after treatment, we know very little about the mechanisms by which it occurs, and we lack strategies to prevent it (22). Currently, antibiotic choice focuses on avoiding antibiotics to which the ongoing infection is already resistant, however, it remains unknown if it is possible to select among the susceptibilitymatched antibiotics in ways that minimize the risk of treatment-induced emergence of resistance at the individual-patient level. To understand and predict personal risk of treatment-induced gain of resistance, we combined whole-genome sequencing of isolates from same-patient recurrent infections with analysis of a longitudinal dataset of UTIs and wound infections collected by Israel’s Maccabi Healthcare Services (MHS) between June 2007 and January 2019. We identified 215,732 MHS patients with at least one record of a UTI (defined as a UTI diagnosis made by a physician followed within 7 days by a positive urine culture with a bacterial count of >105 colonyforming units per milliliter) (figs. S1 and S2) and 20,373 MHS patients with at least one record of a positive wound infection culture. For these patients, we collected clinical data including antibiotic susceptibilities and species identification from all positive cultures, antibiotic purchases, and patient demographics (age, gender, and pregnancy status). For UTI patients, we also collected potential comorbidities of chronic kidney disease and diabetes (23) and records of urinary catheterization (24) (tables S1 and S2). Randomly generated patient identifiers were used to link these different patient records. Resistance profiles were classified in accordance with the Clin-

ical and Laboratory Standards Institute guidelines, with intermediate-level resistance grouped as sensitive. We identified 41,769 untreated UTI cases [defined as a UTI with no antibiotic purchases between 7 days before the sample was taken and the next positive sample or 28 days after the sample was taken (whichever comes first)] and 140,349 single-antibiotic treated cases [where, within 4 days of the sample being taken, one of the eight most frequently prescribed systemic antibiotics was purchased: combination trimethoprim/sulfamethoxazole (sulfa), ciprofloxacin, ofloxacin, combination amoxicillin/clavulanic acid (CA), cefuroxime axetil, cephalexin, nitrofurantoin, or fosfomycin] (table S3). Similarly, for wounds, we identified 7365 infections treated with one of the five most frequently prescribed oral systemic antibiotics (amoxicillin/CA, ciprofloxacin, cefuroxime axetil, cephalexin, and trimethoprim/sulfa). We further categorized these infections by their shortterm clinical outcomes, indicating whether they resulted in an “early recurrence,” defined as a second positive sample recorded within 4 to 28 days after the first positive sample (13,517 treated UTIs, 7933 untreated UTIs, and 442 treated wound infections). Even for treatments correctly matching the susceptibility of the infection, early recurrence was common and was associated with infections gaining treatment-specific resistance. Cases were categorized into six groups on the basis of whether their initial infection was sensitive or resistant to the specified antibiotic (S→ and R→, respectively) and on the basis of their outcome: recurrence with a sensitive infection, recurrence with a resistant infection, or no recurrence (→S, →R, and →∅, respectively) (Fig. 1A). Although susceptibilitymatched antibiotic treatments (S→) had a lower overall rate of recurrence than did mismatched treatments (R→), recurrences were still common (UTIs, 9.2%; wound infections, 5.1%) and frequently gained resistance to the prescribed antibiotic (S→R) (Fig. 1, B and G). Indeed, 30% of all UTI and 19% of all wound infection recurrences gained resistance after antibiotic treatment (S→R), with this fraction strongly varying by antibiotic, reaching as high as 59% (UTIs) and 27% (wounds) of recurrent infections after treatment with the first-line antibiotic ciprofloxacin (Fig. 1, C and H). These gained-resistance cases were strongly associated with treatment, with infections preferentially gaining resistance to the prescribed antibiotic class (Fig. 1, F and I) and temporally peaking soon after the last day of the antibiotic course (Fig. 1E and fig. S4). Compared with untreated cases, susceptibility-matched antibiotic treatment had two counteracting effects: It decreased the overall risk of UTI recurrence (the sum of S→S and S→R) but increased the risk of gained-resistance recurrence (S→R) (Fig. 1D and figs. S5 and S6). 25 FEBRUARY 2022 • VOL 375 ISSUE 6583

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Fig. 1. Posttreatment recurrences are strongly associated with the infection gaining resistance specifically to the treatment antibiotic. (A) Each infection case was categorized into one of six possible groups on the basis of the susceptibility and treatment outcome. (B and G) The overall rate of recurrence for UTIs (B) and wound infections (G) after either susceptibility-matched or susceptibility-mismatched antibiotic treatments. (C and H) The percentage of all antibiotic-treated UTIs (C) and wound infections (H) resulting in early recurrence, and a breakdown of these early recurrences by their pre- and posttreatment susceptibility to the treatment antibiotic, for all treated cases and for each of the most frequently prescribed antibiotics. (D) The rate of early recurrence for UTIs initially sensitive to the specific antibiotic and either treated with this antibiotic (solid bars) or untreated (hashed bars). The cases are further categorized

The large number of correctly treated infections that subsequently gained resistance could be caused by three possible mechanisms: evolution of resistance through mutations, through dedicated resistance genes, or through reinfection with a different strain resistant to the antibiotic (strain replacement) (Fig. 2A). To distinguish between these possibilities in UTIs, we collected 1113 isolates from 510 patients who experienced early UTI recurrence during a 4.5-month period (30 November 2017 to 16 April 2018). We focused on Escherichia coli, which accounts for 70 to 95% of all UTIs (table S4) (4, 22, 25). Sequencing these E. coli isolates, we analyzed the genetic relatedness among same-patient isolates collected before and after treatment and identified any differences in gene content or mutations in antibiotic target and resistance genes (see materials and methods in the supplementary materials). 890

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according to whether they recurred still sensitive to the specified antibiotic (dark blue) or recurred while gaining resistance to it (cyan). Susceptibility-matched treatment decreases the overall risk of early recurrences (down-pointing arrows) yet increases the risk of recurrence with gained resistance (up-pointing arrows). (E) The rate of UTI recurrences occurring on each day after antibiotic treatment (7-day moving average). Each recurrent case is categorized by pre- and posttreatment susceptibility to the prescribed antibiotic, as shown in (A). The dashed vertical line shows the 28-day threshold used to define early recurrences. (F and I) The net change in susceptibility of early recurrent UTIs (F) and wound infections (I). For infections treated with each antibiotic (x axis) or untreated (UTIs), the percentage of gain of resistance (cyan) minus loss of resistance (magenta) to each specified antibiotic is shown (y axis).

The genomic analysis showed that while the same E. coli strain often persists in early UTI recurrences that do not gain resistance, resistance-gaining recurrences were caused by strain replacement. No cases were identified of resistance appearing through point mutations in the originally infecting strain. Analyzing strain relatedness, we found that while reinfection with a different strain was rare in recurrences that did not change resistance to the treatment (19% of S→S or R→R cases), it was the dominant mode in infections gaining resistance (93% of S→R cases; P = 1 × 10−27 compared with cases that did not gain resistance, Fisher test) (Fig. 2, B and C, and table S5). For example, despite the ability of E. coli to readily evolve resistance to ciprofloxacin through point mutations in the target enzymes DNA gyrase subunit A (gyrA) and DNA topoisomerase IV subunit A (parC) in lab conditions

(26), we found that all UTI cases that gained resistance were caused by reinfection with a different strain carrying ciprofloxacin-resistant alleles of gyrA and parC (31 of 31 S→R cases were caused by a different strain compared with 6 of 25 S→S cases; P = 4 × 10−10, Fisher test) (fig. S7) (27). Similarly, while trimethoprim resistance can be acquired through point mutations in the target enzyme dihydrofolate reductase (DHRF) (28), posttreatment resistance was instead conferred by strain replacement (9 of 12 cases) or by the acquisition of a gene encoding a trimethoprim-resistant DHFR enzyme (3 of 12 cases; table S6) (29). Consistent with untreated cases having a much lower rate of gained-resistance recurrence, we found that strain replacement was rare in untreated cases (13%; Fig. 2, D and E). Furthermore, even for antibiotics for which E. coli resistance is rare, such as fosfomycin and nitrofurantoin (fig. S8), science.org SCIENCE

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Fig. 2. Genomic analysis of infecting pathogens before and after antibiotic treatment. (A) Infections that recurred with gained resistance after treatment (cyan) could be a consequence of acquiring resistance-conferring mutations (green lightning bolt), resistance-conferring genes (yellow lightning bolt), or reinfection with a different strain resistant to the antibiotic (dashed arrow). (B and C) Phylogenetic trees of E. coli urine culture isolates collected from patients who experienced early recurrence after treatment with ciprofloxacin (B) or trimethoprim/sulfa (C), with isolate resistance and sensitivity to the prescribed antibiotic indicated by gray and white boxes, respectively. Same-patient isolates are connected with arrows whose color and style represent change in infection susceptibility and mechanism of gain of resistance [as defined in (A)]. Histograms show the genetic distance, in number of single-nucleotide variations (SNVs), between these same patient isolate pairs, again categorized by infection susceptibility and mechanism of gain of resistance [as defined in (A)]. Vertical dashed lines represent the threshold used to define same-strain versus different-strain recurrences. (D and E) Histograms of the genetic distance in SNVs between same-patient isolates in untreated cases categorized by infection susceptibility to ciprofloxacin (D) or trimethoprim/sulfa (E). (F) The percentage of E. coli infections treated with a susceptibility-matched antibiotic that resulted in early recurrence with different nonÐE. coli species (bar patterns), for recurrences that remained sensitive (dark blue) or gained resistance (cyan) to the prescribed antibiotic. (G) The percentage of gained-resistance recurrences in all UTIs and wound infections that were caused by reinfection with a different species.

early recurrence with gained resistance after treatment of an initially sensitive E. coli infection was strongly associated with reinfection with a different resistant strain, yet this time of an entirely different species (Fig. 2F). Overall, 44% of gained-resistance UTI recurrences were caused by a different species (Fig. 2G). A similar pattern was observed for wound infections: Although the rate of change of species was low among recurrent wound infections that remained sensitive to the treatment antibiotic (fig. S9), in most infections that gained SCIENCE science.org

resistance (78%), the species that caused the gain of resistance was not present in the original infection (Fig. 2G). Together, these results suggest that selection for existing resistant strains rather than de novo evolution is the predominant mechanism of treatment-induced emergence of resistance. Given that posttreatment resistance was typically caused by strain or species replacement rather than by spontaneous, and therefore unpredictable, mutations, we wondered whether emergence of resistance may in fact

be predicted at the individual-patient level. As strains are known to recur across same-patient infections even years apart (6), we hypothesized that patients with a history of infections with strains resistant to a given antibiotic are at higher risk of gained-resistance recurrence after susceptibility-matched treatment with that antibiotic (Fig. 3A). To test this hypothesis, we performed multivariate logistic regressions of the risk of recurrence with gained-resistance given patient demographics and past infection history among all infections treated with 25 FEBRUARY 2022 ¥ VOL 375 ISSUE 6583

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Fig. 3. Personalized, antibiotic-specific predictions of treatment-induced emergence of antibiotic resistance. (A) Schematic showing the possible outcomes of susceptibility-matched antibiotic treatment for patients with a recorded history of prior infection susceptibility to the currently prescribed antibiotic. (B) Odds ratio of risk of early recurrence that gained resistance (cyan) or remained sensitive (dark blue) given the patient’s prior history of resistant infections (binary 1/0: any prior resistance to the prescribed antibiotic, or no prior resistance to the prescribed antibiotic). For each antibiotic, all susceptibility-matched treated cases for patients with any prior infections within the past 3 years are considered. Odds ratios are adjusted for demographics (age, gender) and potential risk factors (pregnancy, catheter use). (C) The adjusted odds ratio of early recurrence given the patient’s prior history of resistant infections for all antibiotic treatments combined for both UTIs and wound infections. (D) Timeline of two example patients showing the susceptibilities of their current (t = 0) and prior (t < 0) infections for each antibiotic (white, sensitive; gray, resistant), as well as their ML-predicted probability of recurrence with gained resistance upon treatment of their current infection with each of the antibiotics (circles, green-to-red colormap). Despite both patients being 892

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treated with the same antibiotic to which their infection was sensitive, ciprofloxacin (blue arrow), they had very different ML personal predicted risk of gaining posttreatment ciprofloxacin resistance and indeed varied accordingly in their treatment outcome. (E) The percentage of UTIs within the 14-month test period that gained resistance after treatment for cases prescribed an antibiotic that was not recommended (“unrecommended,” red, 15% highest predicted risk) or recommended (green, 85% lowest predicted risk) by the ML algorithm (these results are robust to the choice of grouping intermediate-level resistance with resistant, fig. S16). (F and G) The overall predicted probability of gaining resistance for all UTIs (F) and wound infections (G) during the test period for four different antibiotic prescription methods: (i) the actual antibiotic prescribed by the physician, (ii) an algorithm that randomly chooses an antibiotic but avoids antibiotics to which the patient had past resistance, and the ML recommendation either (iii) unconstrained or (iv) constrained such that each antibiotic is recommended at the exact same frequency as prescribed by the physicians. The dashed line represents the actual gained-resistance rate for the physician-prescribed antibiotics during the test period. *P < 0.05; **P < 0.005; ***P < 0.0005. science.org SCIENCE

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a susceptibility-matched antibiotic (136,047 UTIs and 5821 wound infections). Despite all of these cases being treated “correctly,” that is, with a susceptibility-matched antibiotic, their risk of recurrence with gained resistance was not uniform: Patients with past infections resistant to the currently prescribed antibiotic were at much higher risk of recurring with gained resistance to the treatment than were patients whose previous infections were sensitive (Fig. 3, B and C; see tables S7 and S8 for regression coefficients). The association between the susceptibility of past infection and the risk of resistance emerging remained significant even for prior infections dating up to 4 years before the current UTI (fig. S10). In contrast, there was no or a much weaker association between past infection susceptibility and risk of early recurrence without gain of resistance, showing that this approach specifically predicts the emergence of resistance rather than merely the risk of early recurrence. A patient’s past infection susceptibility was much more predictive than their past antibiotic purchases, which is consistent with within-host selection for strains persisting in the microbiota rather than de novo resistance evolution driving treatmentinduced gain of resistance (fig. S11). Finally, beyond the important contribution of personal infection history, we also note the contribution of age and gender to risk of treatment-induced gain of resistance (tables S7 and S8). Because some patients were at high risk of their infection gaining resistance to the treatment antibiotic, we asked whether the risk of such gained-resistance recurrences may be reduced with an alternative antibiotic. We developed machine learning (ML) algorithms for personalized antibiotic recommendations that minimize the predicted risk of treatmentassociated emergence of resistance for both UTIs and wound infections (Fig. 3D). For each antibiotic, we trained a logistic regression model to predict the risk of acquiring resistance during or soon after treatment on the basis of patient demographics (age, gender), potential risk factors (pregnancy, catheter use for UTIs), and their record of prior infections, including the number of past sensitive and resistant isolates. Trained on an initial period and then tested on a temporally separated test period (UTIs: 14 months; wound infections: 30 months), the models predict the risk of resistance emergence well (the area under the curve ranged from 0.89 for nitrofurantoin to 0.62 for amoxicillin/CA in UTIs, and from 0.96 for amoxicillin/CA to 0.58 for cefuroxime in wound infections; ofloxacin was not included, because it was not routinely measured during the test period; fig. S12). More practically, binarizing the patient-specific ML predictions for UTIs into high-risk treatments (“unrecommended,” 15% highest MLpredicted risk of gained-resistance recurrence) and lower-risk treatments (“recommended,” SCIENCE science.org

all others), we found that for every antibiotic, patients for whom the prescribed antibiotic was classified as unrecommended by the ML algorithm acquired antibiotic resistance at a significantly higher rate than did those for whom the antibiotic was recommended, even though all of these cases were treated “correctly” with a susceptibility-matched antibiotic (Fig. 3E; the trends are robust with respect to the recommendation threshold; fig. S13). Analyzing all susceptibility-matched treated cases in the test period, we found that in most cases there was an alternative susceptibilitymatched antibiotic that had a lower patientspecific predicted risk of resistance emerging compared with the antibiotic prescribed by the physician (77% of UTIs and 76% of wound infections). Choosing for each patient the antibiotic with the lowest ML-predicted risk of emergence of resistance (ML recommended) reduces the overall risk of emergence of resistance by 70% for UTIs and 74% for wound infections compared with the risk for physicianprescribed treatments (Fig. 3, F and G). Given that many factors contribute to the rate at which physicians prescribe each antibiotic, such as antibiotic efficacy, cost, ease of use, and side effects, we also developed a constrained antibiotic recommendation model that minimizes the risk of emergence of resistance while preserving the same prescription frequency of each antibiotic as prescribed by physicians during the test period (fig. S14) (14). Even these constrained antibiotic recommendations, which merely permute the physicianprescribed antibiotics among patients, can reduce the risk of resistance emerging after treatment by 48% for both UTIs and wound infections compared with the physician-prescribed antibiotics (Fig. 3, F and G). To demonstrate that these constrained recommendations could be made on a case-by-case basis, we also show that the model remains effective when constrained to the physician prescription frequency during a temporally separated period before the final model evaluation period (fig. S14). We note that a simpler algorithm that randomly chooses an antibiotic but avoids antibiotics to which the patient had past resistance can still reduce the risk of resistance emerging after treatment, albeit at a lower frequency than either of the ML models, which is consistent with the contribution of other factors including age, gender, and the more quantitative representation of past infections (Fig. 3, F and G). Furthermore, analyzing the distribution of ML-recommended antibiotics for subsets of patients, such as those with past resistance to a specific antibiotic, may help guide treatment recommendations more broadly (fig. S15). Importantly, the constrained ML models also reduce overall predicted risk of early recurrence (the sum of S→S and S→R), showing that this personalized approach not only reduces gained-

resistance recurrences but, by doing so, may also reduce the overall recurrence risk (fig. S17). While much effort is being invested in methodologies for matching antibiotic treatment to infection susceptibility, susceptibilitymatched treatments often fail, as they select for emergence of resistance by means of reinfection with different strains specifically resistant to treatment. The strong association between such treatment-induced selection for resistance and personal history of past resistant infections suggests a patient-specific strain reservoir. Given the known role that uropathogens and wound pathogens persisting in a patient’s microbiota have in seeding new infections (4–6, 30, 31) and the collateral effect that antibiotics can have on a patient’s microbiome (32–34), it will be interesting to see whether these emerging resistant strains can be detected in a patient’s fecal or skin flora. Regardless of the exact source of these reinfecting resistant strains, our results show that a patient’s past infection susceptibility data and patient demographics can be used to predict early recurrence with gained resistance after susceptibility-matched antibiotic treatment. We hope these results will serve as a basis for a personalized treatment approach that minimizes the selection and spread of resistant pathogens at both the individual-patient and population levels. REFERENCES AND NOTES

1. G. K. M. Harding, A. R. Ronald, Int. J. Antimicrob. Agents 4, 83–88 (1994). 2. W. E. Stamm, S. R. Norrby, J. Infect. Dis. 183 (suppl. 1), S1–S4 (2001). 3. C. P. Montgomery, M. Z. David, R. S. Daum, Curr. Opin. Infect. Dis. 28, 253–258 (2015). 4. L. E. Nicolle, in Brenner and RectorÕs The Kidney, K. Skorecki, G. M. Chertow, P. A. Marsden, A. S. L. Yu, M. W. Taal, Eds. (Elsevier, ed. 10, 2015), pp. 1231–1256. 5. V. L. Tchesnokova et al., Clin. Infect. Dis. 70, 937–939 (2020). 6. B. M. Forde et al., Nat. Commun. 10, 3643 (2019). 7. V. Ki, C. Rotstein, Can. J. Infect. Dis. Med. Microbiol. 19, 173–184 (2008). 8. P. D. Brown, A. Freeman, B. Foxman, Clin. Infect. Dis. 34, 1061–1066 (2002). 9. T. M. Hooton, R. Besser, B. Foxman, T. R. Fritsche, L. E. Nicolle, Clin. Infect. Dis. 39, 75–80 (2004). 10. Y. G. Kwak et al., Infect. Chemother. 49, 301–325 (2017). 11. H. Goossens, M. Ferech, R. Vander Stichele, M. Elseviers; ESAC Project Group, Lancet 365, 579–587 (2005). 12. C. Costelloe, C. Metcalfe, A. Lovering, D. Mant, A. D. Hay, BMJ 340, c2096 (2010). 13. R. Colodner, I. Kometiani, B. Chazan, R. Raz, Infection 36, 41–45 (2008). 14. I. Yelin et al., Nat. Med. 25, 1143–1152 (2019). 15. J. P. Metlay, B. L. Strom, D. A. Asch, J. Antimicrob. Chemother. 51, 963–970 (2003). 16. U. D. Allen, N. MacDonald, L. Fuite, F. Chan, D. Stephens, CMAJ 160, 1436–1440 (1999). 17. J. Ena, C. Amador, C. Martinez, V. O. de la Tabla, C. M. Kunin, J. Urol. 153, 117–120 (1995). 18. L. Johnson et al., Am. J. Med. 121, 876–884 (2008). 19. H. C. Baggett et al., J. Infect. Dis. 189, 1565–1573 (2004). 20. J. A. Silverman, H. L. Schreiber 4th, T. M. Hooton, S. J. Hultgren, Curr. Urol. Rep. 14, 448–456 (2013). 21. R. Ikäheimo et al., Clin. Infect. Dis. 22, 91–99 (1996). 22. K. Gupta et al., Clin. Infect. Dis. 52, e103–e120 (2011). 23. R. Ikram, R. Psutka, A. Carter, P. Priest, BMC Infect. Dis. 15, 224 (2015). 24. W. J. Burman et al., Am. J. Med. 115, 358–364 (2003).

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25. A. L. Flores-Mireles, J. N. Walker, M. Caparon, S. J. Hultgren, Nat. Rev. Microbiol. 13, 269–284 (2015). 26. F. Collin, S. Karkare, A. Maxwell, Appl. Microbiol. Biotechnol. 92, 479–497 (2011). 27. E. Zankari et al., J. Antimicrob. Chemother. 72, 2764–2768 (2017). 28. E. Toprak et al., Nat. Genet. 44, 101–105 (2011). 29. E. Zankari et al., J. Antimicrob. Chemother. 67, 2640–2644 (2012). 30. M. Magruder et al., Nat. Commun. 10, 5521 (2019). 31. K. L. Nielsen, P. Dynesen, P. Larsen, N. Frimodt-Møller, J. Med. Microbiol. 63, 582–589 (2014). 32. L. Dethlefsen, S. Huse, M. L. Sogin, D. A. Relman, PLOS Biol. 6, e280 (2008). 33. M. Yassour et al., Sci. Transl. Med. 8, 343ra81 (2016). 34. E. G. Pamer, Science 352, 535–538 (2016). 35. M. Stracy, R. Kishony,Technion-Kishony-lab/Antibiotic-treatmentfailure: Code for Stracy et al,Science 2022, version 1, Zenodo (2021); https://doi.org/10.5281/zenodo.5799077. ACKN OW LEDG MEN TS

Funding: This work was supported by National Institutes of Health grant R01 GM081617 (R.Ki.); Israel Science Foundation grant 3055/19 within the Israel Precision Medicine Partnership program

(R.Ki.);, Ernest and Bonnie Beutler Research Program of Excellence in Genomic Medicine (R.Ki.); European Research Council FP7 ERC grant 281891 (R.Ki.); Wellcome Trust Sir Henry Wellcome fellowship 204684/Z/16/Z (M.S.); and D. Dan and Betty Kahn Foundation’s gift to the University of Michigan, Weizmann Institute, and Technion–Israel Institute of Technology Collaboration for Research. Author contributions: M.S., O.S., I.Y., G.K., J.K., G.C., V.S., and R.Ki. designed the study. R.Ka. and E.H. curated clinical data. M.P., G.R., T.W., O.S., and Y.A. collected clinical samples. G.R., T.W., G.K., and J.K. handled clinical project administration. M.S., O.S., I.Y., and Y.A. performed whole-genome sequencing. M.S. and R.Ki. analyzed the data. M.S., I.Y., O.S., B.F., M.P., G.C., V.S., and R.Ki. interpreted the results. M.S. and R.Ki. wrote the paper with comments from all authors. Competing interests: The authors declare that they have no competing interests. Data and materials availability: The clinical data that support the findings of this study are available from Maccabi Healthcare Services, but restrictions apply to the availability of these data, which were used under license for the current study and so are not publicly available. Access to the data is, however, available upon reasonable request and signing a material transfer agreement with Maccabi Healthcare Services. Analysis code is available from https://github.

ORGANIC CHEMISTRY

Total synthesis of himastatin Kyan A. DÕAngelo1, Carly K. Schissel1, Bradley L. Pentelute1,2,3,4*, Mohammad Movassaghi1* The natural product himastatin has an unusual homodimeric structure that presents a substantial synthetic challenge. We report the concise total synthesis of himastatin from readily accessible precursors, incorporating a final-stage dimerization strategy that was inspired by a detailed consideration of the compoundÕs biogenesis. Combining this approach with a modular synthesis enabled expedient access to more than a dozen designed derivatives of himastatin, including synthetic probes that provide insight into its antibiotic activity.

T

he proliferation of multidrug-resistant pathogenic bacteria is widely recognized as a threat to global health (1, 2). Natural products have served as the primary inspiration for new antibiotics to treat bacterial infections (3). (–)-Himastatin (1) is a macrocyclic peptide with a homodimeric structure isolated from Streptomyces himastatinicus (Fig. 1) that demonstrates antibiotic and antitumor activity (4–6). Although (–)-himastatin’s (1) mechanism of action is not known, an early investigation demonstrated that its antibiotic activity was reduced in the presence of sodium salts of phospholipids and fatty acids, leading to speculation that (–)-himastatin (1) may target the bacterial membrane (7). (–)-Himastatin’s (1) homodimeric structure does not resemble those of any well-characterized antibiotic class, including known membrane-disrupting cyclic peptides. The most distinctive structural feature of (–)-himastatin (1) is the central C5–C5′ linkage between cyclotryptophan residues that is formed in the final biosynthetic step (8) and is critical for the observed Gram-positive antibiotic 1

Department of Chemistry, Massachusetts Institute of Technology, Cambridge, MA 02139, USA. 2The Koch Institute for Integrative Cancer Research, MIT, Cambridge, MA 02142, USA. 3Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA. 4Center for Environmental Health Sciences, MIT, Cambridge, MA 02139, USA. *Corresponding author. Email: [email protected] (M.M.); [email protected] (B.L.P.)

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activity (9). Related monomeric natural products discovered after (–)-himastatin (1), including (–)-NW-G01 (S2), show a substantial enhancement in antibiotic activity upon chemoenzymatic dimerization (10) (fig. S1). Other notable structural features of (–)-himastatin (1) include the alternating sequence of D- and L-amino acids, a depsipeptide linkage, and the piperazic acid residue with g-hydroxylation. Danishefsky’s landmark synthesis of (–)himastatin (1), which clarified the Ca stereochemistry of the cyclotryptophan residue, featured an early-stage Stille coupling to form the central C5−C5′ linkage followed by bidirectional elaboration of a dimeric cyclotryptophan (9). Early-stage formation of this linkage also featured in total syntheses of the related natural product (–)-chloptosin (S1) by Yao (11) and Ley (12) and their co-workers, who found that cross-coupling approaches to achieve a more attractive late-stage dimerization (which would also offer access to heterodimeric derivatives) were not successful (12). Motivated by the distinctive structure, established synthetic challenge, and antibiotic activity, we became interested in developing a concise total synthesis of (–)-himastatin (1) that would offer rapid access to derivatives for chemical biology studies. The key unaddressed challenge of uniting two complex fragments to form the C5−C5′

com/Technion-Kishony-lab/Antibiotic-treatment-failure (35). All urine culture isolate whole-genome sequencing data generated in this study have been deposited in the Sequence Read Archive database and are available here:www.ncbi.nlm.nih.gov/sra/ PRJNA786867. Treatment and susceptibility data for the sequenced isolates are provided in the supplementary materials (data S1). SUPPLEMENTARY MATERIALS

science.org/doi/10.1126/science.abg9868 Materials and Methods Supplementary Text Figs. S1 to S17 Tables S1 to S8 References (36–38) MDAR Reproducibility Checklist Data S1

10 February 2021; resubmitted 7 September 2021 Accepted 23 December 2021 10.1126/science.abg9868

bond at the center of (–)-himastatin’s (1) dimeric structure encouraged us to consider the development of a new synthetic methodology. To address the Csp2–Csp2 linkage present in (–)-himastatin (1), we needed to identify a strategy that stands apart from our group’s prior approaches based on reductive or photolytic radical generation and coupling to secure Csp3–Csp3 linkages and Csp3–Csp2 linkages between similar (13) and dissimilar fragments (14). We began with a detailed examination of (–)-himastatin’s (1) biosynthesis from a linear peptide 4 that is cyclized and then subjected to oxidative tailoring by three cytochrome P450 enzymes (8). The final step, catalyzed by HmtS, forges the central C5–C5′ bond by oxidative dimerization of (+)-himastatin monomer (2). On the basis of recent theoretical studies of P450catalyzed C–C bond formation, we envisioned that this enzymatic dimerization may take place via radical–radical coupling of two cyclotryptophan radicals (fig. S2) (15, 16). These radical species are likely generated in rapid succession via indoline N–H hydrogen-atom abstraction at the heme active site, before undergoing combination in its vicinity (16, 17). We envisioned that a biosynthetically inspired chemical method for the oxidative dimerization of cyclotryptophans could follow the same radical–radical coupling blueprint. As opposed to hydrogen atom abstraction, we planned to generate an analogous open-shell cyclotryptophan species via single-electron oxidation of the embedded aniline substructure. Consistent with studies of aniline dimerization via singleelectron oxidation (18–20), we predicted that the resulting arylamine radical cation would rapidly dimerize at the most accessible position, forming the desired C5–C5′ linkage. Late-stage application of this chemistry to dimerization of (+)-himastatin monomer (2) permits a straightforward modular assembly of linear hexadepsipeptide 5 akin to native precursor 4, without the constraints imposed science.org SCIENCE

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Fig. 1. Comparison of the biogenesis of himastatin and our bioinspired synthetic strategy. MIC values for (Ð)-himastatin (1) are taken from (4) against Grampositive bacteria. MIC, minimum inhibitory concentration. Protein Data Bank identification codes: HmtT, 4GGV; HmtN, 5WX2; HmtS, 5Z9I.

by bidirectional elaboration of a simple dimeric cyclotryptophan (9, 11, 12). Direct union of complex peptide macrocycles also offers the elusive opportunity to access heterodimeric derivatives of (–)-himastatin (1). Our dimerization method required the identification of a single-electron oxidant that would target the aniline substructure within a complex cyclotryptophan precursor (21). Existing precedent for the use of inorganic oxidants for generation of aniline radical cations (20) ultimately guided our initial selection of reagents. We found that excess silver(I) hexafluoroantimonate [5 equivalents (equiv.)], in combination with the non-nucleophilic pyrimidine base TTBP (22) in 1,2-dichloroethane, could effect C5−C5′ dimerization of cyclotryptophan, cyclotryptamine, and indoline derivatives (Fig. 2A). In each case, a single regioisomer consistent with a symmetric C5−C5′ linked homodimer was isolated. Single-crystal xray diffraction of dimeric endo-diketopiperazine (+)-7h verified the expected connectivity. The use of an aqueous sodium thiosulfate reductive workup was critical for optimal isolation of the dimers, as a second equivalent of oxidant is consumed owing to their sensitivity toward further oxidation under the reaction conditions (23, 24). We found that exo-configured diketopiperazines 6e and 6g were subject to complete oxidation in approximately half the time of their corresponding endo-derivatives 6f and 6h, respectively. This finding correlates SCIENCE science.org

with the increased accessibility of the N1 locus in substrates 6e and 6g, the site of initial oxidation (25). Substitution of N1 with a methyl group in the case of indoline 6k did not inhibit the dimerization, consistent with a radical intermediate as opposed to a closed-shell arenium cation (26). As part of our optimization efforts (table S1) (23) and to expand the range of reagents that could be used in more complex applications of our dimerization method, we also investigated the use of copper(II) salts as single-electron oxidants (20). Cyclotryptophan dimer (–)-7a could be obtained by using catalytic copper(II) trifluoromethanesulfonate and silver(I) carbonate as the terminal oxidant, albeit in lower yield (34%, 18% recovered starting material) compared to stoichiometric AgSbF6 (54%, 53% on a 0.50-mmol scale). To investigate the mechanism of this C−C bond–forming dimerization reaction, we devised a series of experiments using indoline substrates (Fig. 2B and fig. S3) (23). When an equimolar mixture of C2-methyl and C2-phenyl indolines 6i and 6j, respectively, was subjected to our dimerization conditions, we observed a statistical mixture of homo- and heterodimers arising from similar rates of single-electron oxidation (Fig. 2B, green; fig. S3, eq. 1). However, oxidative dimerization of an equal mixture of indolines 6j and 6k gave predominantly (90%) homodimer formation, along with a trace (4%) amount of heterodimer 7n (fig. S3, eq. 2). When a limiting quantity of oxidant was used,

we determined that these indoline substrates were consumed sequentially, with N1-methyl indoline 6k dimerizing selectively over NH indoline 6j (Fig. 2B, blue, and fig. S3, eq. 3). Having observed homodimerization of a more readily oxidized monomer in the presence of a similarly nucleophilic but less readily oxidized monomer, we conclude that C5−C5′ bond formation preferentially occurs through radical– radical coupling rather than nucleophilic capture. This conclusion is consistent with the absence of adduct formation in the homodimerization of cyclotryptophan 6a despite the presence of external p-nucleophiles (e.g., methallyltrimethylsilane, dimethylketene silyl acetal, N-trimethylsilylindoline) and is reinforced by prior studies demonstrating that radical– radical coupling between aniline radical cations is fast (k = ~107 M–1•s–1 for the dimerization of PhNMe2•+) (18–20). We postulate that the high local concentration of radical species near the surface of the oxidant favors their direct combination over nucleophilic pathways (14, 20). In the context of our synthetic efforts, the rapid rate and apparent insensitivity of the radical–radical coupling manifold to nucleophilic interference bode well for the application of this chemistry to complex substrates. These findings highlight a possible underlying parallel between our oxidative dimerization methodology and our mechanistic proposal for the biosynthetic dimerization catalyzed by HmtS (fig. S2), involving 25 FEBRUARY 2022 • VOL 375 ISSUE 6583

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successive generation of radical species in close proximity to each other. For the synthesis of (+)-himastatin monomer (2), we sought to leverage the practical advantages of solid-phase peptide synthesis (27), offering rapid and customizable access to complex peptides by minimizing repetitive purification and isolation steps. In contrast to the reported solution-based approach to intermediates en route to (–)-himastatin (1) (9), we relied on a hybrid solution–solid phase synthetic strategy. The resin-bound D-threonine 9 (Fig. 3) was elaborated with L-leucine (–)-10 and tri-

depsipeptide fragment (+)-8, the latter being prepared in one step (23) (78% yield) from a depsipeptide block (23, 28) (three steps from commercial carboxylic acids) and known Ne, O-protected D-5-hydroxypiperazic acid S8 (9) (nine steps from 4-pentenoic acid). The crude pentadepsipeptide acid (+)-11 obtained upon cleavage was then coupled with cyclotryptophan (–)-12 [fig. S4; five steps from commercial tryptophan derivative (–)-S3, 60% yield], affording linear hexadepsipeptide (–)-13 in 64% overall yield from threonine resin 9 (23). The efficient hybrid synthetic strategy we have

Fig. 2. Oxidative dimerization of cyclotryptophan, cyclotryptamine, and indolines. (A) Substrate scope of our oxidative dimerization reaction. In the ORTEP representation of dimeric endo-diketopiperazine (+)-7h, the thermal ellipsoids are drawn at 30% probability, and only selected hydrogen atoms are shown. (B) Mechanistic studies using equimolar mixtures of differentially substituted indolines provide evidence for a radicalÐradical coupling mechanism. Reagents and conditions: AgSbF6, TTBP, ClCH2CH2Cl, 23°C; * copper (II)-catalyzed conditions: Cu(OTf)2 (20 mol %), Ag2CO3, ClCH2CH2Cl, 23°C. TES, triethylsilyl; TTBP, 2,4,6-tritert-butylpyrimidine. 896

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developed enabled convergent assembly of intermediate hexadepsipeptide (–)-13 with only a single chromatographic purification, which compares favorably to linear solutionphase synthesis, which requires at least 10 separate steps to access an intermediate of similar complexity (9). Furthermore, our modular strategy allows for conducting difficult couplings in solution (28) and introducing the tryptophan residue as a cyclotryptophan to bypass stereoselectivity concerns that would arise from late-stage oxidation (29). Following termini deprotection, linear peptide (–)-13 was cyclized to (+)-himastatin monomer (2) in 49% overall yield (Fig. 3), affording the immediate biosynthetic precursor to (–)-himastatin (1). All 1H and 13C nuclear magnetic resonance (NMR) data, as well as optical rotation for synthetic monomer (+)-2, were consistent with literature values (8, 9). Having accessed (+)-himastatin monomer (2), we focused on the application of our biosynthetically inspired oxidative dimerization methodology to complete the total synthesis of (–)-himastatin (1) (Fig. 3). Although silver(I) hexafluoroantimonate and copper(II) trifluoromethanesulfonate were effective for the dimerization of simpler cyclotryptophans (Fig. 2A), they gave little to no oxidation of the cyclotryptophan incorporated within the more complex (+)-himastatin monomer (2). We hypothesized that aggregation and inactivation of these insoluble oxidants, combined with the lower reactivity of complex macrocyclic peptide substrates, may be responsible for the low conversion, and we sought to address the challenge posed by evaluating other single-electron oxidants. Consistent with this hypothesis, insoluble oxidants such as other Ag(I,II) and Cu(II) salts were generally ineffective. However, soluble oxidants, including organic radical cations such as magic blue [(4-BrPh)3N•+SbF6], did provide oxidation, but products derived from nucleophilic substitution of the C–Br bond (SNAr) by the peptide dominated (21). Informed by our prior use of Cu(II) for the dimerization of simpler substrates and in search of an oxidant with both good solubility and low propensity toward nucleophilic capture, we identified copper(II) hexafluoroantimonate. Our isolation of freshly prepared Cu(SbF6)2, commonly used as a soluble Lewis acid catalyst (30), provided us with an opportunity to investigate its use as a stoichiometric oxidant. In the event, exposure of (+)-himastatin monomer (2) to excess Cu(SbF6)2 (20 equiv.) and DTBMP (4 equiv.) in 1,2-dichloroethane afforded (–)-himastatin (1) in 40% yield (3 mg), with only trace ( 64 mg/ml) (fig. S5 and table S11). In addition to TAMRA, homodimeric himastatin analogs derived from other fluorophores were also found to be inactive (fig. S5). Consistent with our expectation that minimizing the overall perturbation of himastatin’s structure to only one half of the dimer may preserve antibiotic activity, we found that the MIC of TAMRA-heterodimer (–)-25 (Fig. 4B) was indeed comparable to that of (–)-himtastatin (1) in B. subtilis (6 versus 1 mg/ml). Thus, the opportunity for heterodimer formation offered by our biogenetically inspired late-stage dimerization methodology was instrumental to secure access to a fluorescent himastatin probe (37), as well as other key derivatives including meso-himastatin (1) that would otherwise be challenging to prepare by chemoenzymatic or bidirectional synthesis (9, 10). Other structural features specific to (–)himastatin (1) include a depsipeptide linkage and 5-hydroxypiperazic acid residue. Evaluating the derivatives that we prepared to study these particular structural features, we observed a trend of decreasing antibiotic activity 898

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when the ester linkage was replaced with either a secondary amide (–)-15 or tertiary amide (–)-17, consistent with the loss of a hydrogen-bond site (38). Furthermore, when the 5-hydroxypiperazic acid residue was replaced with a proline residue, antibiotic activity was completely abolished. Although proline residues are known to induce turn formation, especially when the adjacent amino acid is of opposite a-stereochemistry, they do not exhibit a rigidifying effect as pronounced as that seen in N-acyl piperazic acid derivatives (39). Consistent with the predicted loss of rigidity upon proline substitution, NMR spectra of homodimer (–)-19 and monomer (+)-18 in various solvents at 23°C revealed the presence of minor conformers not observed in the spectra of (–)-himastatin (1) or our other derivatives. Taken together, these results provide evidence that structural rigidity, enforced by hydrogen-bonding and conformational restriction, is important to himastatin’s antimicrobial mode of action. Confocal microscopy has been used to observe the biological effects of antibiotics on B. subtilis, including the first approved membrane-disrupting lipopeptide, daptomycin (37). We sought to use our synthetic compounds in conjunction with this experimental approach to further characterize the antibiotic activity of (–)-himastatin (1). Our synthetic heterodimeric probe, TAMRA-himastatin (–)-25, offered an opportunity to directly visualize its interaction with bacteria and monitor cellular localization. When B. subtilis cells were treated with either 8 or 16 mg of TAMRA-himastatin (–)-25 per milliliter of solution, we observed substantial accumulation in the bacterial envelope (fig. S6A), with little to no intracellular staining seen at the lower concentration. More cells were stained with TAMRA-himastatin

(–)-25 at the lower concentration than at the higher, but a smaller proportion of the stained cells exhibited visible membrane defects (23). The most intense sites of staining were observed at bacterial septa, in addition to patches of stain along sidewalls. At the higher concentration (fig. S6B), defects such as membrane extrusions coincided with lateral accumulation of TAMRA-himastatin (–)-25. These sites of curvature appear to reflect areas where the antibiotic has induced changes to membrane morphology. The staining pattern observed with TAMRAhimastatin (–)-25 was similar to that of the membrane stain FM4-64 with unmodified himastatin (1) (fig. S7). Untreated B. subtilis cells have smooth membranes and normal septal rings, but cells treated with a sublethal concentration of either enantiomer of himastatin (1) display pronounced membrane defects, notably patches of membrane thickening. Furthermore, the observed similarity in membrane morphology between himastatin (1) enantiomers appears to be consistent with their similar antibiotic activity. In a separate experiment, we evaluated the time scale by which (–)-himastatin (1) acts on bacteria at lethal concentrations (fig. S8). When treated with (–)-himastatin (1) at a concentration twice the MIC value, bacterial membranes were permeabilized within 30 min, as indicated by influx of the viability stain SYTOX Green. The observations of our microscopy studies are comparable to those seen with daptomycin despite a lack of structural similarity to himastatin (37). The membrane defects and localization patterns observed in B. subtilis with unmodified (–)-himastatin (1) and our fluorescent himastatin derivative (–)-25 show science.org SCIENCE

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Table 1. Antibiotic evaluation of himastatin derivatives and probes against Gram-positive bacteria. MIC values were determined by using the brothmicrodilution method; see table S11. MRSA, methicillin-resistant Staphylococcus aureus; MSSA, methicillin-sensitive S. aureus; VRE, vancomycin-resistant Enterococcus; VSE, vancomycin-sensitive Enterococcus.

MIC (mg/ml) Compound

Monomer

MIC (mg/ml)

B. subtilis

Dimer

B. subtilis

MRSA

MSSA

VRE faecalis

VSE faecalis

S. himastatinicus

(–)-himastatin (+)-2 >64 (–)-1 1 2 1 1 1 8 ............................................................................................................................................................................................................................................................................................................................................ ent-(+)-himastatin (–)-2 >64 (+)-1 0.5 2 2 2 1 1 ............................................................................................................................................................................................................................................................................................................................................ meso-himastatin – – meso-1 1 2 1 1 1 4 ............................................................................................................................................................................................................................................................................................................................................ rac-himastatin (±)-2 >64 (±)-2 0.5 2 2 1 1 2 ............................................................................................................................................................................................................................................................................................................................................ Single-residue substitutions ............................................................................................................................................................................................................................................................................................................................................ L-Val (+)-14 >64 (–)-15 8 64 16 32 16 >64 ............................................................................................................................................................................................................................................................................................................................................ Me L- Val (+)-16 >64 (–)-17 >64 >64 >64 >64 >64 >64 ............................................................................................................................................................................................................................................................................................................................................ D-Pro (+)-18 >64 (–)-19 >64 >64 >64 >64 >64 >64 ............................................................................................................................................................................................................................................................................................................................................ L-Ser(OMe) (+)-20 >64 (–)-21 2 4 4 1 2 8 ............................................................................................................................................................................................................................................................................................................................................ L-Lys(N3) (+)-22 >64 (–)-23 2 2 2 2 1 8 ............................................................................................................................................................................................................................................................................................................................................ L-Lys(TAMRA) (+)-24 >64 (–)-25 6 >64 >64 16 16 – ............................................................................................................................................................................................................................................................................................................................................

resemblance to those seen with unmodified and fluorescent forms of daptomycin, respectively (37). Furthermore, the short time scale of membrane permeabilization following treatment with himastatin (1), like that seen after treatment with daptomycin, is consistent with a mode of action based on physical perturbations (33, 37). This mode of action is distinct from that of certain other Gram-positive peptide antibiotics, such as vancomycin and teixobactin, that interfere with cell-wall biosynthesis and have kill times longer than 30 min (40). Separately, the similarity in MIC values and cellular morphology among our series of synthetic himastatin stereoisomers reveals that achiral interactions—for example, with the hydrophobic groups of phospholipids (34, 35)— are largely responsible for the observed antibiotic activity. In summary, our chemical biology studies using our synthetic probes offer findings that are consistent with the hypothesis that (–)-himastatin’s (1) antibiotic activity is dependent on interaction with bacterial membranes (7). It is evident that (–)-himastatin (1) is a distinct member among known membrane disruptors (41). Published preclinical studies of (–)-himastatin’s (1) biological activity are limited to early reports primarily focused on its antitumor activity (4, 7). For instance, it was found that intraperitoneal administration of (–)-himastatin (1) prolonged the life span of mice inoculated with leukemia or melanoma cells, with toxicity being observed at the highest doses evaluated (4). Against the backdrop of escalating antibiotic resistance, we aim to continue detailed study and evaluation of (–)-himastatin's (1) antibiotic activity and application of new insights in SCIENCE science.org

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We thank W. C. Salmon at the W. M. Keck Microscopy Facility (Whitehead Institute) for assistance with confocal microscopy; C. Tsay and P. Müller (Massachusetts Institute of Technology) for assistance with single-crystal x-ray diffraction of (+)-7h; and R. P. Bhattacharyya (Massachusetts General Hospital) for providing several bacterial strains. We are grateful to J. S. Albin (Massachusetts General Hospital) for helpful discussions. Funding: This study was supported by NIH grants GM-089732 and GM-141963 (M.M.); an NSERC postgraduate scholarship, grant PGSD3-502869-2017 (K.A.D.); and an NSF graduate research fellowship, grant 1122374 (C.K.S.). Author contributions: K.A.D. and M.M. conceived the project and designed the synthetic routes; K.A.D. performed the chemical synthesis; C.K.S. performed the antibiotic assays and fluorescence microscopy; all coauthors wrote and edited the manuscript. Competing interests A patent application covering this work has been filed by MIT (US patent application no. 63/153,286). Data and materials availability: Experimental procedures, spectroscopic data, and copies of NMR spectra are available in the supplementary materials. Structural parameters for endo-diketopiperazine (+)-7h are freely available from the Cambridge Crystallographic Data Centre under CCDC-2099734. SUPPLEMENTARY MATERIALS

science.org/doi/10.1126/science.abm6509 Materials and Methods Figs. S1 to S13 Tables S1 to S11 References (41–49) Spectral Data 1 October 2021; accepted 21 December 2021 10.1126/science.abm6509

25 FEBRUARY 2022 • VOL 375 ISSUE 6583

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Advancing Sustainable Technologies Through Catalysis

Bioorganic Chemistry

• Ca2+ Channels Henry Colecraft, Juan Du, Xiaowei Hou, Jean-Ju Chung

Assaf Gal

Leslie Leinwand, Thomas Eschenhagen

Chan, Yamuna Krishnan, Paul Richardson, David Savage, Xin Zhang

• The GRC Power Hour™ Louise Charkoudian, Alexis Komor

Bridging Scientific Disciplines to Understand Biomineral Formation in Breadth and Depth

• Cellular and Genetic Control of Mineral Deposition Tali

• Keynote Session: From Primary Mechanism to Targeted

CHAIRS: Christopher Johnson and Arica Beisaw

Biomineralization

• Regulation of Morphogenesis Nils Kröger, Jaroslaw Tyszka,

Thomas Vondriska, Laura Zelarayán, Timothy McKinsey, Gabriele Schiattarella, William Pu, Vassilios Bezzerides

• Cellular Imaging and Engineering Stephen Fried, Jefferson

• Microbes as Drivers of Winter Biological Processes Bjorn Robroek, Hannah Carey, Mats Oquist

Asnani, Javid Moslehi, Rudolf de Boer, Anja Karlstaedt

• Novel Approaches to Targeted Therapies Lucie Carrier,

• The GRC Power Hour™

Mulder, Heidi Steltzer

• Consequences of Fluctuating Temperatures During

Mathias Mericskay, Catalina Vasilescu, Johannas Backs, Yibin Wang

• Cancer and the Heart David Eisner, Sumanth Prabhu, Aarti

Therapies for Cardiomyopathies Benjamin Prosser, Rong Tian,

PROCTOR ACADEMY, ANDOVER, NH CHAIRS: Brent Sinclair and Sapna Sharma VICE CHAIRS: Pamela Templer and Steven Cooke

Oligotrophication in the Northern Hardwood Forest Steven

Mechanisms John Elrod, Elizabeth Murphy, Danielle Murashige,

Schindl, Yousang Gwack, Khaled Machaca, Paul Rosenberg Vennekens, Ivana Kuo

• Mitochondrial Ion Channels Madesh Muniswamy, Anna Raffaello, Luca Scorrano, John Elrod, Lan Wei-LaPierre, Dipayan Chaudhuri

• Intracellular Ion Channels Antony Galione, Sandip Patel, Irina Serysheva, Sebastian Brauchi

• Calcium Signaling and Neuro(patho)physiology Cecilia Hidalgo, Hilmar Bading, Elizabeth Jonas, Brian Bacskai, Wayne Chen, Claudio Hetz

Catalysis Vassiliki-Alexandra Glezakou, Karsten Reuter, Joel Schmidt, Toshiaki Taniike, Hongliang Xin Zaera, An-Hui Lu, Charles Sykes, Praveen Bollini

• Catalysis with Alternative Energy Inputs Eranda Nikolla, Kyoung-Shin Choi, Suljo Linic, William Schneider

• Dynamic Catalytic Behavior Beata Kilos-Reaume, Anastassia Alexandrova, Norbert Kruse, Omar Abdelrahman

• Insights from Mechanistic Investigations Philippe Sautet, Rebecca Fushimi, Rachel Getman, Emiel Hensen, Justin Notestein

• Operando Characterization of Catalysts John Lockemeyer, Juan Bravo-Suarez, Angelika Brückner, Ambarish Kulkarni

• Alternative Feedstocks for Manufacturing Daniel Resasco, Oliver Gutierrez-Tinoco, Feng Wang, Karen Wilson

• Keynote Session: Integration of Experiment, Computation

and Theory Javier Guzman, Dion Vlachos • The GRC Power Hour™ Beata Kilos-Reaume, Eranda Nikolla

• Calcium Sensors Loren Looger, Yubin Zhou, Yan Zhang, Arnab Mukherjee • Calcium Signaling and Disease Barbara Niemeyer, Johanna Lanner, Natasha Prevarskaya, Saverio Gentile, Ágnes Enyedi, Michal Hershfinkel

• Keynote Session: Local Calcium Signaling in Plasticity and

Disease Ilya Bezprozvanny, Richard Tsien • The GRC Power Hour™

Catalysis Designing Catalysts to Advance Sustainable Energy and Chemical Production JUN 18-19, 2022 CHAIRS: Brandon Bukowski and Sarah Specht

Sturm (née Rosseeva), Tamara Alliston

• Biomineralization Principles Translated Maisoon Al-Jawad, Luiz Bertassoni, Ben Wang

• Biominerals in Pathology Willi Jahnen-Dechent, Peter Vekilov, Sunita Ho, Eileen Shore

• Keynote Session: Geochemistry, Proxies and

Evolution Derk Joester, Andrew Knoll, Alex Gagnon • The GRC Power Hour™ Netta Vidavsky, Alex Gagnon

Biomineralization A Multifaceted Approach Toward Understanding Biomineral Formation Pathways and Purposes AUG 13-14, 2022 CHAIRS: Dimitra Athanasiadou and Konrad Hedderick

Cardiac Regulatory Mechanisms

Cell Biology of the Neuron

Applying High Resolution Approaches to Complex Cardiac Disorders: Towards Targeted Therapies

The Impact of Neuronal Shape, Structure and Size on Neuronal Function in Health and Disease

JUN 26-JUL 1, 2022 COLBY-SAWYER COLLEGE, NEW LONDON, NH CHAIRS: Jil Tardiff and Christoph Maack VICE CHAIRS: Rong Tian and Benjamin Prosser

• Cardiac Repair and Regeneration Bjorn Knollmann, Jop van Berlo, Bin Zhou, Jennifer Davis, Mauro Giacca, Wolfram Zimmerman

• Myocellular Structural Dynamics in Health and

Disease Jolanda van der Velden, Jennifer Van Eyk, Farah Sheikh, Brett Colson, Maria Kontaridis, Wolfgang Linke

• Excitation-Contraction Coupling and Arrhythmias Donald Bers, Steven Houser, Isabelle Deschenes, Sara Liin, Xander Wehrens, Matthew Daniels

JUN 26-JUL 1, 2022 WATERVILLE VALLEY, WATERVILLE VALLEY, NH CHAIRS: Kang Shen and Valeria Cavalli VICE CHAIRS: Monica Driscoll and Patrik Verstreken

• Keynote Session: Neuronal Cell Biology and Diseases Yishi Jin, Kelsey Martin, Matthew Rasband

• Controlling Neuronal Shape, Size and Repair Binhai Zheng, Mike Fainzilber, Alyson Fournier, Oren Schuldiner, Marc Hammarlund

• Gene Regulation and Phase Transition in Health and

Disease Pietro De Camilli, Antonella Riccio, Mingjie Zhang, Lin Mei

• Synaptic Transmission Patrik Verstreken, Matthew Dalva, Camin Dean, Matthijs Verhage, Ege Kavalali

• Mitochondria and Cytoskeleton Antonina Roll-Mecak, Richard Youle, Andrew Carter, Lukas Kapitein

• Membrane Trafficking and Transport Thomas Schwarz, Rejji Kuruvilla, Giampietro Schiavo, Bettina Winckler, Erika Holzbaur

• Translation and Protein Homeostasis in Health and

• Polarity Transitions During Disease Terry Lechler, Gillian Griffiths, Carole Parent, Erik Sahai

• Asymmetric Division and Stem Cells Dominique Bergmann, Renata Basto, Xin Chen, Ahna Skop, Sander van den Heuvel

Nicola Allen, Aiman Saab, Marc Freeman, Michael Granato

• Keynote Session: New Technologies in Neuronal Cell

Biology Erik Jorgensen, Edward Boyden, Xiaowei Zhuang • The GRC Power Hour™ Rejji Kuruvilla, Cagla Eroglu

Cell Biology of the Neuron Molecular Understanding of the Neuron: Development, Plasticity and Function

Diverse Fungi as Innovative Models for Understanding Genomics, Pathogenicity and Signaling JUN 25-26, 2022

• Tissue Homeostasis: Wound Healing and Extrusion Carole Parent, William Bement, Anne Classen, Jody Rosenblatt

CHAIRS: Abigail LaBella and Charles Puerner

• The GRC Power Hour™

Disease Monica Driscoll, Andrew Dillin, Anne Bertolotti, Jeffery Twiss • Neuron-Glia Interaction and Communication Cagla Eroglu,

Cellular and Molecular Fungal Biology

Centromere Biology Cell Polarity Signaling

Evolution, Structure, Regulation and Function of Centromeres in Health and Disease

Cell Polarity Across Developmental Time and Space

JUL 24-29, 2022 MOUNT SNOW, WEST DOVER, VT CHAIR: Sylvia Erhardt VICE CHAIR: Iain Cheeseman

MAY 28-29, 2022 CHAIRS: Melissa Pickett and Andrew Tilston-Lunel

Cell-Cell Fusion

NEW!

• Keynote Session: Centromeres: From Evolution to Human

Health Iain Cheeseman, Genevieve Almouzni, Harmit Malik

Diverse Organisms and Common Mechanisms in Cell-Cell Fusion

• Biophysical Properties of Centromeres Stephen Harrison, • Centromeres in Meiosis and Stem Cell Division Arshad

Cell Death

JUN 5-10, 2022 STONEHILL COLLEGE, EASTON, MA CHAIR: Elizabeth Chen VICE CHAIR: Mark Rose

Cell Death-Associated Inflammation in Disease

• Keynote Session: Mechanism and Aftermath of Membrane

JUN 25-26, 2022 CHAIRS: Chinyere Agbaegbu Iweka and Oshri Avraham

MAY 15-20, 2022 LES DIABLERETS CONFERENCE CENTER, LES DIABLERETS, SWITZERLAND CHAIR: Francis Chan VICE CHAIR: Pascal Meier

• Keynote Session: Perspectives on the Mechanism and

Function of Cell Death in Physiology Pascal Meier, Vishva Dixit, Marion MacFarlane

• Inflammation and Tissue Homeostasis Andrew Oberst, John Silke, Manolis Pasparakis, Andreas Villunger

• Immunogenic Cell Death Hiroyasu Nakano, Carla Rothlin, Julie Magarian Blander, Peter Vandenabeele

• Fundamental Mechanisms of Cell Death Carla Rothlin, Ana Garcia-Saez, Xiaodong Wang, J. Marie Hardwick

• Cell Death in Neuroinflammation and Neurological

disorders Stephen Tait, Junying Yuan, Marc Freeman • Cell Death in Immunity Elizabeth Hartland, Seamus Martin, Domagoj Vucic, Henning Walczak

• Non-Apoptotic Forms of Cell Death Ana Garcia-Saez, Eric Baehrecke, Marcus Conrad, Stephen Tait

• Harnessing Cell Death Mechanisms in Cancer Julie Magarian Blander, John Abrams, Anne Hamacher-Brady, Andreas Strasser

• Infectious Diseases and Cell Death John Silke, Elizabeth Hartland, Andrew Oberst, Feng Shao

• The GRC Power Hour

™

Marion MacFarlane, Anne Hamacher-Brady

Fusion Mark Rose, Jennifer Lippincott-Schwartz, Axel Brunger • Intracellular Membrane Fusion Jennifer Lippincott-Schwartz, Arun Anantharam, Katja Faelber, Junjie Hu, Erdem Karatekin, Ling-Gang Wu

• Virus-Cell Fusion Benjamin Podbilewicz, Gregory Melikian, Yorgo Modis, James Munro, Felix Rey

• Cell-Cell Fusogens Joshua Zimmerberg, Roy Duncan, Thomas Krey, Douglas Millay, William Snell, Hongmei Wang, Benjamin Podbilewicz

• Membrane Adhesion in Cell Fusion N. Louise Glass, Naokazu Inoue, Andrea Pauli, Leonid Chernomordik

• Actin Cytoskeleton in Cell Fusion Stefanie Sprunck, Ori Avinoam, Mary Baylies, Jean-Francois Cote, Daniel Fletcher, Guangshuo Ou, Sophie Martin Michael Kozlov, Harvey McMahon, Huanghe Yang, Joshua Zimmerberg

• Diverse Cell Fusion Systems Sophie Martin, Sigal Ben-Yehuda, Don Fox, N. Louise Glass, Massimo Hilliard, Vicki Losick, Stefanie Sprunck

• Cell Fusion and Disease Harvey McMahon, Melissa Wong, Chiara Zurzolo, Fernando Rodriguez-Perez

Cellular and Molecular Fungal Biology Understanding Fungal Function and Diversity: Complex Communities, Pathogenicity and Bioresources

MAY 14-15, 2022

• Fungal Hijacking and Host Manipulation João Araújo, Charissa de Bekker, Carolyn Elya, Pietro Spanu

• Cellular Organization and Molecular Biology James Kronstad,

Cell Polarity Signaling Dynamics of Cell Polarity MAY 29-JUN 3, 2022 COLBY-SAWYER COLLEGE, NEW LONDON, NH CHAIR: Jeremy Nance VICE CHAIR: Yukiko Yamashita

• Polarity Within and Across Cells Yukiko Yamashita, Denise Montell, Geraldine Seydoux

• Dynamics of Cell Polarization Danelle Devenport, Dominique Bergmann, Clemens Cabernard, Daniel Lew, Edwin Munro

• Polarity Transitions During Development Sander van den Heuvel, Jessica Feldman, Jean-Léon Maître, Ulrich Tepass

• Cell Polarization and the Cytoskeleton William Bement, Julie Canman, Gregg Gundersen, Stephanie Gupton, Terry Lechler

• Polarity and Morphogenesis: Eggs and Embryos Jessica Feldman, Otger Campas, Sally Horne-Badovinac, Yu-Chiun Wang

• Polarity and Morphogenesis: Tissues and Organs Sally Horne-Badovinac, Michel Bagnat, Danelle Devenport, Shigeo Hayashi, Jeff Rasmussen

Defects and Disease Ben Black, Daniele Fachinetti, Hironori Funabiki, Beth Sullivan

• Centromere Genomics, Evolution and Variability Steven Henikoff, Luca Comai, Ines Drinnenberg, Karen Miga

• Epigenetic Regulation of Centromere Identity Patrick Heun, Daniel Foltz, Fangpu Han, Barbara Mellone, Yael Nechemia-Arbely

• Transcripts and Transcription Control of Centromere

Function Claire Francastel, Robin Allshire, Michael Blower, Dawn Carone, Rachel O'Neill • Building Blocks Around and Above the Centromere Ann Ehrenhofer-Murray, Jennifer Deluca, Tatsuo Fukagawa, Dean Dawson

• New Concepts of Centromere Function and

Regulation Lars Jansen, Aaron Straight, Needhi Bhalla, Lilian Kabeche • The GRC Power Hour™ Elaine Dunleavy, Rachel O'Neill

Centromere Biology Regulating Centromere Function Through Structure JUL 23-24, 2022 CHAIRS: Samuel Corless and Maiko Kitaoka

• The GRC Power Hour™ Mary Baylies, Mark Rose

Mechanisms of Cell Death in Homeostasis and Disease CHAIRS: Katherine Stewart and Florian Bock

Desai, Julia Cooper, Elaine Dunleavy, Yukiko Yamashita, Binyam Mogessie

• Centromere Dysfunction: Chromosome Segregation

• Membrane Organization and Lipids Leonid Chernomordik,

JUN 26-JUL 1, 2022 HOLDERNESS SCHOOL, HOLDERNESS, NH CHAIRS: Jason Stajich and Alexandra Brand VICE CHAIRS: Nick Talbot and Anna Selmecki

Cell Death

Ekaterina Grishchuk, Michael Lampson, Andrea Musacchio, David Barford

Amy Gladfelter, Josh Nosanchuk, Gero Steinberg, Duncan Wilson, Lillian Fritz-Laylin, Robert Arkowitz

• Fungal Mutualism and Symbiotic Interactions Christine Voisey, Gregory Bonito, Jana U'Ren, Anna Rosling

• Genomic Perspectives on Fungal Evolution Christina Cuomo, David Hibbett, Bridget Barker, Iulian Ene, Daniel Croll, Annegret Kohler, Antonis Rokas

• Fungi in the Microbiome and Complex Communities Anthony Amend, Nina Gunde-Cimerman, Iliyan Iliev, Teresa Pawlowska, Michelle Afkhami

• Fungal Virulence and Drug Resistance Elaine Bignell, Antonio Di Pietro, Jeniel Nett, Johanna Rhodes, Carol Munro, Tamara Doering, Mike Bromley

• Fungi as Bioresources Nancy Keller, Jason Slot, Isabelle Benoit Gelber • Sensing, Signaling and Development Alexander Idnurm, Yi Liu, Janet Quinn, Michael Freitag, Neil Brown, Daniel Kornitzer, Lauren Ryder, Julia Schumacher

• Late-Breaking Topics Nick Talbot, Anna Selmecki • The GRC Power Hour™ Elaine Bignell, Christina Cuomo

Chemistry and Biology of Tetrapyrroles The Roles of Tetrapyrroles in Catalysis, Regulation, Metabolism and Disease JUL 17-22, 2022 SALVE REGINA UNIVERSITY, NEWPORT, RI CHAIR: Emma Raven VICE CHAIR: Amy Medlock

• New Structural Techniques for the Study of

Tetrapyrroles Syun-Ru Yeh, Wyatt Yue, Allen Orville, Hitomi Sawai • Trafficking, Signalling and Regulation by Heme Elizabeth Boon, Emily Weinert, Hiroaki Kitagishi, Dennis Stuehr, Andrew Hudson

• The Biogenesis and Functions of Bilins J. Clark Lagarias, Lin Liu, Tammi Richardson, William Lanzilotta

• Tetrapyrroles in Human Health and Disease Peter Meissner, Makiko Yasuda, Levi Wood, Diane Ward

• The Biology of Tetrapyrroles: Catalysis, Mechanism and

Regulation Aimin Liu, John Groves, Brian Crane • B12: Biosynthesis, Transport, Pharmacology and

Mechanistic Enzymology Stephen Ragsdale, Dorota Gryko, Alison Smith, Ritimukta Sarangi, Tessa Young

• Regulation and Biosynthesis of Chlorophyll

Pigments Jennifer Bridwell-Rabb, Min Chen, Jean Alric, Neil Hunter • Microbial Tetrapyrrole Metabolism Mark Shepherd, Celia Goulding, Stefan Hofbauer, Juliette Lecomte

• Keynote Session: Tetrapyrrole Regulation and

Homeostasis Samuel Beale, Angela Wilks, Mark O'Brian

Chemotactic Cytokines Orchestrating Cell Migration and Location in Health and Disease JUN 12-17, 2022 LES DIABLERETS CONFERENCE CENTER, LES DIABLERETS, SWITZERLAND CHAIR: Marcus Thelen VICE CHAIR: Ronen Alon

• Keynote Session: Chemokines in Rare Diseases Tracy Handel, Philip Murphy, Gerry Graham

• Chemokine Receptor-Dependent Signal

Transduction Bernhard Moser, Mario Mellado, Silvano Sozzani, Michel Bouvier, Mette Rosenkilde

• Structures and In Silico Modeling Mette Rosenkilde, Tracy Handel, Thomas Schall, Brian Volkman

• Chemokine-Mediated Cell Migration Daniel Legler, Philippe Bousso, Holger Knaut, Carole Parent, Tal Arnon

“

GRC cultivates an environment conducive to interdisciplinary learning and scientific discovery by fostering interactions among senior and junior academics, scientists at government laboratories and industrial associates from all over the globe.

”

DR. MONICA OLVERA DE LA CRUZ, Northwestern University

• Atypical Chemokine Receptors Gerry Graham, Daniel Legler, Martyna Szpakowska, Ralf Stumm

• Chemokines in Cancer Thomas Schall, Aleksandra Ozga, Burkhard Ludewig, Adit Ben-Baruch, Ann Richmond

• Chemokines in Pathologies Mariagrazia Uguccioni, Joanna Groom, Hai Qi, Paul Proost

• Chemokines in Health and Disease Philip Murphy, Amanda Burkhardt, Davide Robbiani, Christoph Scheiermann, Reinhold Förster

• Keynote Session: Chemokines in Immune Responses Ronen Alon, Eugene Butcher, Sussan Nourshargh, Antal Rot

• The GRC Power Hour™ Ann Richmond

JUN 26-JUL 1, 2022

Jadwiga Richter, Karen Rosenlof

Robert Wood, Blaz Gasparini

• Climate Impacts Daniel Schrag, Jonathan Proctor, Long Cao • Developing World Impacts Michael Taylor, Ines Camilloni, Izidine Pinto

• Engineering and Design Hugh Hunt, Frank Keutsch, Ben Kravitz, Wake Smith

• Keynote Session: Transdisciplinary Research for Climate

Engineering Holly Buck, David Keith • The GRC Power Hour™ Simone Tilmes, Ulrike Lohmann

• Chromatin Assembly, Replication and Repair Peter Becker,

Claire Rougeulle, Tony Kouzarides, William Greenleaf

• Chromosomes and Genome Architecture Karolin Luger, Edith

Climate Engineering Physical Processes and Impacts of Radiation Management Approaches to Climate Change

Oded Rechavi, Raul Mostoslavsky, Shelley Berger, Andreas Ladurner

• Reprogramming and Regeneration Joanna Wysocka, Anne Ferguson-Smith, Yi Zhang, Bradley Cairns, Amanda Fisher, Alexander Meissner

• Chromatin and Disease Mechanisms Karen Adelman, Sharon Dent, Ali Shilatifard, Joanna Wysocka, Cigall Kadoch

• Chromatin Biophysics Geeta Narlikar, Xavier Darzacq, Ibrahim Cisse, Michael Rosen, Leonid Mirny, Zhucheng Chen

• Transcription and Post-Transcriptional Events Ibrahim Cisse, Karen Adelman, Hiroshi Kimura, Dirk Schubeler, Jerry Workman

• The GRC Power Hour™ Claire Rougeulle, Karen Adelman

CHAIRS: Katie Dagon and Daniele Visioni

Colloidal Semiconductor Nanocrystals Nanocrystal Chemistry, Physics and Applications JUL 3-8, 2022 LES DIABLERETS CONFERENCE CENTER, LES DIABLERETS, SWITZERLAND CHAIRS: Maksym Kovalenko and Matt Law VICE CHAIRS: Gordana Dukovic and Efrat Lifshitz

• Synthesis Science Brandi Cossairt, Uri Banin, Elena Shevchenko • Bioapplications Carlos Toro, Allison Dennis, Inge Herrmann, Wolfgang Parak, Teresa Pellegrino

• Assemblies and Collective Phenomena Dmitri Talapin, Sara

Chromatin Structure and Function

Bals, Christophe Delerue, Christopher Murray, Nuri Yazdani

Micro to Macro Chromatin Structure in Epigenetics and Disease

• Charge, Energy and Heat Transport Vanessa Wood, Maria

MAY 28-29, 2022

• Photophysics Mikhail Zamkov, Daniel Gamelin, Zeger Hens, Patanjali

CHAIRS: Robert Porter and Jumana AlHaj Abed

JUL 17-22, 2022 REY DON JAIME GRAND HOTEL, CASTELLDEFELS, SPAIN CHAIRS: Adrian Roitberg and Zoe Cournia VICE CHAIR: Natalie Fey Cavalli, Adrian Mulholland, Marco De Vivo, Syma Khalid, Darrin York

Calculations Chris Chipot, Hugo Gutierrez-De-Teran, Xinjun Hou, William Jorgensen, Henry Woodcock

Materials and Interfaces Spiridoula Matsika, Ana Nicoleta Bondar, Gerald Tanoury, Sotiris Xantheas Pablo Dans

• Modeling Functional Materials Fernanda Duarte, Seonah Kim, Edward Sherer

• Using Machine Learning for Molecular Design Natalie Fey, Tatjana Braun, Gianni De Fabritiis, Olexander isayev, Frank Noe

• Integrating Big Data in Drug Discovery Applications: From

Allostery to Biologics Design Kenneth Merz, Ivet Bahar, Chris de Graaf, Masha Niv, Rebecca Wade

• Multiscale Modeling for Computer-Aided Drug

Design Simone Fulle, Ronald Knegtel, Silvia Lovera, Jeremy Smith • Modeling Long-Scale Conformational Dynamics Julien Michel, Cecilia Clementi, Karissa Sanbonmatsu

• The GRC Power Hour™ Syma Khalid, Zoe Cournia

Computational Chemistry How Computational Method Development Translates into Application JUL 16-17, 2022 CHAIRS: Anna Kamenik and Taylor Quinn

JUN 25-26, 2022

Heard, Wendy Bickmore, Peter Fraser, Ting (C-ting) Wu, Peter Becker

• Chromatin, Metabolism and Physiology Robert Kingston,

Multiscale Modeling of Complex Systems: Methods and Applications

• Modeling Nucleic Acids Modesto Orozco, Thomas Cheatham,

• Climate Response Ulrike Niemeier, Peter Irvine, Daniele Visioni

• Histone and RNA Modifications Wendy Bickmore, Jeannie Lee,

Computational Chemistry

• Keynote Session: Climate Engineering in Context Mark

• Cloud-Mediated Processes Thomas Leisner, Daniel Rosenfeld,

Thomas Jenuwein, Robert Kingston, Danny Reinberg, Caroline Dean, Steven Jacobsen

CHAIRS: Xing Yee Gan and Joo Yeon Roh

• From Quantum Dynamics to Multiscale Modeling of

JUN 11-12, 2022

Karolin Luger, Craig Peterson, Shiv Grewal

JUL 2-3, 2022

GRAND SUMMIT HOTEL AT SUNDAY RIVER, NEWRY, ME CHAIRS: Douglas MacMartin and Trude Storelvmo VICE CHAIRS: Simone Tilmes and Ulrike Lohmann

• Regional Methods Olivier Boucher, Kate Ricke, Sonia Seneviratne

• Remodeling Chromatin Structure Ali Shilatifard, Carl Wu,

Light-Matter Interactions in Semiconductor Nanomaterials

• Methods and Applications in Free Energy

Chemokine Structure, Function and Receptor Interactions in Homeostasis and Disease

MAY 29-JUN 3, 2022 REY DON JAIME GRAND HOTEL, CASTELLDEFELS, SPAIN CHAIR: Asifa Akhtar VICE CHAIR: Geeta Narlikar

Colloidal Semiconductor Nanocrystals

• Linking Molecular Structure and Dynamics to Function Andrea

Lawrence, Piers Forster, Alan Robock

Chromatin Modifications, RNA and Metabolism

Sionnest, Wolfgang Heiss, Gerasimos Konstantatos, Emmanuel Lhuillier

• The GRC Power Hour™ Gordana Dukovic, Efrat Lifshitz

Processes and Impacts of Radiation Management Approaches to Climate Change

• Stratospheric Processes Valentina Aquila, Gabriel Chiodo,

Chromatin Structure and Function

Demir, Eunjoo Jang, Sohee Jeong

• Nanocrystals for the Infrared Javier Vela, Philippe Guyot-

Climate Engineering

Chemotactic Cytokines

CHAIRS: Acacia Dishman and Gillian Wilson

• Optoelectronics Maria Antonietta Loi, Sergio Brovelli, Hilmi Volkan

Ibanez, Cherie Kagan, Lea Nienhaus, Marcus Scheele Kambhampati, Victor Klimov

• Towards Quantum Light Sources Matthew Sheldon, Moungi Bawendi, Yoshihiko Kanemitsu, Brahim Lounis, Peter Sercel

• Photochemistry and Energy Conversion Raffaella Buonsanti, Jillian Dempsey, Prashant Kamat, Susanna Thon, Emily Weiss

Computational Materials Science and Engineering

NEW!

Comparing Theories, Algorithms and Computation Protocols in Materials Science and Engineering JUL 31-AUG 5, 2022 GRAND SUMMIT HOTEL AT SUNDAY RIVER, NEWRY, ME CHAIR: Rampi Ramprasad VICE CHAIRS: Katsuyo Thornton and Heather Kulik

• Synthesis Planning Algorithms Wenhao Sun, Elsa A. Olivetti, Connor Coley

• Machine Learning Bryce Meredig, Subramanian K. R. Sankaranarayanan, Klaus-Robert Müller, Rama Vasudevan

• Coarse Graining James Warren, Nikolas Provatas, Gregory Voth • Concurrent and Hierarchical Multiscale Modeling Kaushik Dayal, David McDowell, Martin Steinhauser, Ellad Tadmor

• Non-Adiabatic Quantum Mechanics Claudia Draxl, André Schleife, Priya Vashishta

• Autonomous Robotic Systems Christoph Kreisbeck, Andy Cooper, A. Gilad Kusne, Loïc Roch

• Calculation of Phase Diagrams (CALPHAD) Raymundo Arroyave, Ursula Kattner, Axel van de Walle

• Materials by Design Alejandro Strachan, Juan de Pablo, James Saal, Cormac Toher

• Quantum Computing Hanhee Paik, Alan Aspuru-Guzik, Veera Sundararaghavan

• The GRC Power Hour™ Jennifer Carter, Aeriel Leonard

Correlated Electron Systems Topology and Correlations: Long-Range Entanglement in Many-Body Systems JUN 26-JUL 1, 2022 MOUNT HOLYOKE COLLEGE, SOUTH HADLEY, MA CHAIRS: Nandini Trivedi and James Analytis VICE CHAIRS: Senthil Todadri and Suchitra Sebastian

• Magic Angles and Correlations in Moire Materials Cory Dean, Dmitri Efetov, Andrea Young, Ashvin Vishwanath

• Moire Mohit Randeria, Oskar Vafek, Shahal Ilani, Kwabena Bediako, Jie Shan • Quantum Spin Liquids Yuan-Ming Lu, Donna Sheng, Minoru Yamashita, Vesna Mitrovic

• Quantum Oscillations in Insulators Natalia Perkins, Roser Valenti, Nai Phuan Ong, Hide Takagi, Ciaran Hickey

• Fractionalization and Anomalous Thermal Hall Ehud Altman, Mitali Banerjee, Gael Grissonnanche, Yuji Matsuda

• Non-Fermi Liquids Subir Sachdev, Martin Zwierlein, Andy Lucas, Anaëlle Legros, Achim Rosch

• Non-Equilibrium and Non-Linear Response Aashish Clerk, David Hsieh, Vedika Khemani, Norman Yao

• Quantum Dynamics and Measurement Michel Devoret, Crystal Noel, Valla Fatemi, Giulia Semeghini, Jason Alicea

• Late-Breaking Topics Senthil Todadri • The GRC Power Hour™ Colette Patt

Correlated Electron Systems Emergent Electronic Order, Fractionalization and Long-Range Entanglement in Quantum Materials JUN 25-26, 2022 CHAIRS: Ali Husain and Debanjan Chowdhury

Cyclic Nucleotide Phosphodiesterases Probing and Targeting PDEs: From Local Control of Signaling Nanodomains to Functional Impact JUN 19-24, 2022 LES DIABLERETS CONFERENCE CENTER, LES DIABLERETS, SWITZERLAND CHAIRS: Jos Prickaerts and Jin Zhang VICE CHAIRS: Viacheslav Nikolaev and Michy Kelly

• Cyclic Nucleotide Signaling Pathways: From Receptors to

Targets David Kass, Carmen Dessauer, Martin Lohse, Susan Taylor, Martina Schmidt

• Spatiotemporal Regulation of Cyclic Nucleotide Signaling Viacheslav Nikolaev, Manuela Zaccolo, John Scott, Aldebaran Hofer, Mark Gomelsky

• Structural, Molecular and Systems Dissection of PDE

Signaling Nikolai Artemyev, Rick Cote, Ganesh Anand • Cyclic Nucleotide Signaling in Cardiovascular Systems Rodolphe Fischmeister, Christina Kruuse, Yang Xiang, Xiaodong Cheng, Chen Yan, David Kass

• Novel and Atypical Signaling Manuela Zaccolo, Roland Seifert, David Baker, Nikolai Artemyev

• Selective PDE Targeting of Central Nervous System Functions Michy Kelly, Achim Schmidtko, Dorit Ron, Pierre Vincent, Jan Kehler

• PDEs in Vascular and Metabolic Processes Enno Klussmann, Donald Maurice, Mary Anna Venneri, Anders Tengholm, Alexander Pfeifer

• PDE Mediated Signaling in Immunological and

Inflammatory Processes Joseph Beavo, Hai-Bin Luo, Gretchen Snyder, Stefan Brocke, Kjetil Tasken, Ralf Hoffmann

• Therapeutic Considerations and Path to the Clinic Gretchen Snyder, Coleen Atkins, George Baillie

• The GRC Power Hour™ Michy Kelly, Viacheslav Nikolaev

Cyclic Nucleotide Phosphodiesterases Phosphodiesterases: From Fundamental Insights to Therapeutic Targets JUN 18-19, 2022

Crystal Engineering Inspired Design, Assembly and Properties of Molecular Materials JUN 19-24, 2022

CHAIRS: Melissa Schepers and Amy Tibbo

Cytoskeletal Motors

Deep Carbon Science Exploring Fluxes, Forms and Origins of Deep Carbon in Earth and Other Terrestrial Planets JUN 19-24, 2022 BATES COLLEGE, LEWISTON, ME CHAIRS: Edward Young and Kai-Uwe Hinrichs VICE CHAIRS: Tamsin Mather and Doug LaRowe

• Origins of Carbon in the Solar System Mary Voytek, Bernard Marty, Siyi Xu, Lauren Cleeves

• Earth's Deep Carbon Cycle Michael Walter, Andrea Giuliani, Graham Pearson, Jonathan Tucker

• Extreme Physics, Chemistry and Biology of Carbon Jie Li, Razvan Caracas, Susannah Dorfman, Jung-Fu Lin

• New Tracers of the Provenance of Hydrocarbons Jeanine Ash, Max Lloyd, Thomas Giunta, Jeffrey Marlow, Jill McDermott

• Serpentinization and Deep Life Matthew Schrenk, Susan Lang, Florence Schubotz

• Life at its Limits Doug LaRowe, Brandy Toner, Fengping Wang, Daan Speth

• Connections Between Deep Carbon and Atmospheres Tamsin Mather, Peter Barry, Oliver Shorttle

• The Fate of Carbon During Subduction Terry Plank, Megan Duncan, Matthieu Galvez, Craig Manning, Paul Wallace

• Late-Breaking Topics Rachel Harris • The GRC Power Hour™

Deep Carbon Science Carbon at the Intersection of the Biosphere and Geosphere JUN 18-19, 2022 Chairs: Jonathan Tucker and Rachel Harris

Defects in Semiconductors Defect Formation, Characterization, Control and Utilization AUG 14-19, 2022 COLBY-SAWYER COLLEGE, NEW LONDON, NH CHAIR: Jeffrey McCallum VICE CHAIR: Kai-Mei Fu

• Developments in Defect Spectroscopy and

Metrology Lasse Vines, Darshana Wickramaratne, Jean-Philippe Tetienne

GRAND SUMMIT HOTEL AT SUNDAY RIVER, NEWRY, ME CHAIR: Jennifer Swift VICE CHAIR: Andy Cooper

Molecular Machines: From Biophysics To Physiology To Disease JUL 10-15, 2022

Materials for Quantum Applications Marina Radulaski, Cyrus

• Order, Disorder and Defects Aurora Cruz-Cabeza, Karena

MOUNT SNOW, WEST DOVER, VT CHAIR: Steven Rosenfeld VICE CHAIR: Margaret Titus

Dreyer, Chitraleema Chakraborty

Chapman, Ying Diao

• Crystal Assembly Braulio Rodriguez-Molina, Katharina Edkins, Matteo Salvalaglio, Jeffrey Rimer, Karah Knope

• Polymorphs and Mixtures Yu-Sheng Chen, Robert Schurko, Sara Weaver

• Crystals Under Pressure Bruno Hancock, Iain Oswald, Jack Clegg, Franziska Emmerling, Daniel Hooks

• Crystal Reactivity Pance Naumov, Kana Sureshan, Jason Benedict • Pharmaceuticals and Cocrystals Rositza Petrova, Changquan Sun, Doris Braun, Lynne Taylor

• Big Data and Informatics Susan Reutzel-Edens, Ian Bruno • Porosity and Open Framework Materials Brian Smith, Kim Jelfs, Chenfeng Ke, Craig Brown, Katherine Mirica

• Engineering Across Length Scales Kristin Hutchins, Benjamin Palmer

• The GRC Power Hour™ Susan Reutzel-Edens

• Keynote Session: Motors Working in a Context Margaret Titus, Vladimir Gelfand, Kathleen Trybus

• Motors in Cardiovascular Disease David Warshaw, Anne Houdusse, James Spudich, Theresia Kraft, Sanford Bernstein

• Structure and Regulation Carolyn Moores, Ahmet Yildiz, Anthony Roberts, Hernando Sosa, Stefan Raunser

• Motors in Cell Motility and Transport James Sellers, David Warshaw, Richard Cheney, Samara Reck-Peterson, Erika Holzbaur

• Modeling and Analysis of Molecular Motor Systems Erkan Tuzel, David Odde, Tamara Bidone, Michael Murrell, Michael Diehl

• Motor Generated Forces in Cell Function Sarah Heissler, Michael Ostap, Ewa Paluch, Andre Levchenko, Dylan Burnette

• Tracks and Filaments Antonina Roll-Mecak, Anna Kashina, Enrique De La Cruz, Jennifer Ross, Casper Hoogenraad

• Motors in Cancer, Psychiatric, Metabolic, and Infectious

Diseases Lee Sweeney, Anne Bresnick, Jonathan Kirk, Dominique

Crystal Engineering

• Color Centers in Wide Band-Gap Semiconductors and 2D

• Characteristics of Defects in 2D Materials and Oxide

Semiconductors Joel Varley, Matt McCluskey, John Lyons, Prineha Narang

• Spin Centers: Spectroscopy and Applications Takeshi Ohshima, Sophia Economou, Alexander Weber-Bargioni, Stefania Castelletto

• Defects in Nitride Semiconductors Mary Ellen Zvanut, Ramon Collazo, Annemarie Exarhos

• Defects in Photovoltaic Materials and Devices,

Identification and Control John Murphy, Hele Savin, Vladan Strevanovic, Wolfram Kwapil

• Defect Characterization and Control Elif Ertekin, Anyao Liu, Atsushi Oshiyama, Jinwoo Hwang

• High Resolution Imaging and Characterization of

Defects Paul Koenraad, Lorenzo Rigutti • Keynote Session: Toward Single Defect Imaging in Layered

and 3D Materials Kai-Mei Fu, Jianwei Miao • The GRC Power Hour™ Kai-Mei Fu

Soldati-Favre, Michael Way, Courtney Miller

Engineering Crystals in the Fourth Dimension: Monitoring of Structural Changes in Crystals

• Motors in Mitosis Jason Stumpff, Ekaterina Grishchuk, Tarun Kapoor,

JUN 18-19, 2022

• The GRC Power Hour™

Sophie Dumont, William Bement

CHAIRS: Ivana Brekalo and Ren Wiscons

Cytoskeletal Motors Molecular Motors and Their Tracks: Biophysics, Physiology, and Disease JUL 9-10, 2022 Chairs: Ashley Arthur and Donte Stevens

Defects in Semiconductors Defect Formation, Characterization, Control and Utilization AUG 13-14, 2022 Chairs: Hongling Lu and Ymir Frodason

Diffraction Methods in Structural Biology

Drug Carriers in Medicine and Biology

Breaking Down the Barriers in Structural Biology into Defined, Measurable and Solvable Problems

Enabling New Therapies Through Drug Carrier Design

Strategies to Disrupt Resistance in Infectious Diseases, Cancer and Agriculture

JUL 31-AUG 5, 2022 MOUNT SNOW, WEST DOVER, VT CHAIRS: Suzie Pun and Samir Mitragotri VICE CHAIRS: Kathryn Whitehead and Vadim Dudkin

JUN 26-JUL 1, 2022 BRYANT UNIVERSITY, SMITHFIELD, RI CHAIRS: Lizbeth Hedstrom and Daruka Mahadevan VICE CHAIRS: Aaron Goldman and Alexis Kaushansky

• Keynote Session: Drug Carriers Revolutionizing

• Keynote Session: Protecting New Drugs and Pesticides

JUL 24-29, 2022 BATES COLLEGE, LEWISTON, ME CHAIR: James Holton VICE CHAIR: Janet Newman

• Artificial Intelligence in Structural Biology Airlie McCoy, Ho Leung Ng, Christopher Watkins

• Optimal Data Collection Limited by Damage, Equipment

and Sample Quality Ana Gonzalez, Elspeth Garman, Kunio Hirata, Gleb Bourenkov

• Sample Prep with Uncooperative Molecules Alex McPherson, Sarah Bowman, Anchi Cheng

• Processing Algorithms for Difficult Data Kay Diederichs, Dominika Borek, Loes Kroon-Batenburg, Derek Mendez, Jeney Wierman

• Massive Radiations: Electrons and Neutrons Garib Murshudov, Wah Chiu, Johan Hattne, Flora Meilleur

• Interpreting Low-Resolution Maps and Weak Data Paul Emsley, Tristan Croll, Jane Richardson, Isabel Uson

• Divining Ligands with Confidence Dorothee Liebschner, Tom Peat, Frank von Delft

• Selected Poster Presentations Edward Snell • The Last Angstrom: Disorder, Dynamics and

Function Helen Ginn, Andrea Thorn, Henry van den Bedem, Rozaliya Barabash

Therapeutic Approaches Vladimir Muzykantov, Dennis Lee, Paula Hammond, David Mooney

• New Materials for Drug Delivery Ester Kwon, Paul Wender, Kristy Ainslie, Jianjun Cheng, Jean-Christophe Leroux

• Advances Toward Translation and Carrier Interactions with

the Immune System Elizabeth Nance, Jinming Gao, Anna Schwendeman

• Drug Carriers in Oncology Rizia Bardhan, Natalie Artzi, Debra Auguste, Tatiana Novobrantseva, Anand Subramony

• Cell-Mediated Drug Delivery Juliane Nguyen, Zhen Gu, Elena Batrakova

• Intracellular Delivery of Biologics Michael Mitchell, Julie Champion, Craig Duvall, Richard Wooster

• Selected Poster Presentations Vadim Dudkin, Kathryn Whitehead • Biological Carriers Olivia Merkel, David Schaffer, Laura Ensign, Don Hilvert, Nicole Steinmetz

• Overcoming Barriers to Oral Delivery Omid Veiseh, Maria Jose Alonso, Sujatha Sonti, Giovanni Traverso

• The GRC Power Hour™ Kristy Ainslie

Drug Resistance

Against Resistance Alexis Kaushansky, Alina Baum, Seva Rostovtsev

• The Emergence of Resistance Pradipsinh Rathod, Sophie Helaine, Houra Merrikh, Susan Rosenberg, Sarah Amend

• Eco-Evolutionary Strategies to Address Resistance Andriy Marusyk, Eugene Shakhnovich, Jacob Scott

• Combating Resistance with Novel Targets Mithila Jugulam, Emily Derbyshire, Eachan Johnson, Mark Rolfe, Paul Workman

• Durable Drug Design Timothy Wencewicz, David Epstein, Adam Palmer

• Systems and Modeling Strategies to Address Resistance Adam Palmer, Nitin Baliga, Funda Meric-Bernstam, Pamela Yeh

• Threats and Responses Funda Meric-Bernstam, Sarat Chandarlapaty, Pradipsinh Rathod

• Microbiome and Resistance Celia Schiffer, Christopher Ford, Neha Garg, Yoshitomo Kikuchi, Peter Belenky

• Keynote Session: Emerging Strategies to Combat

Resistance Aaron Goldman, Richard Alm, Paul Turner, James Welsh • The GRC Power Hour™

• The GRC Power Hour™ Elspeth Garman

Drug Carriers in Medicine and Biology Diffraction Methods in Structural Biology

Exploring Size-Based Delivery Strategies for Biologics and Novel Drug Cargos

Data-Rich Experiments in Serial Crystallography, Time-Resolved Studies and MicroED

JUL 30-31, 2022

JUL 23-24, 2022 Chairs: Jennifer Wierman and James Parkhurst

DNA Topoisomerases in Biology and Medicine Topoisomerase Mechanism, Function and Inhibition: From Single-Molecule Analyses to Clinical Trials AUG 7-12, 2022 BRYANT UNIVERSITY, SMITHFIELD, RI CHAIRS: Lynn Zechiedrich and Keir Neuman VICE CHAIRS: Yuk-Ching Tse-Dinh and Dagmar Klostermeier

• Keynote Session: Molecular Mechanisms to Clinical

Trials Valakunja Nagaraja, Sue Jinks-Robertson, Yves Pommier • Topoisomerases as Targets for Antimicrobial Agents Marc Drolet, Alexandra Aubry, Pan Chan, Neil Osheroff

• Processing of Topoisomerase Adducts Hannah Klein, Heidrun Interthal, Robert Van Waardenburg

• Interplay Between Genome Topology and Topoisomerase

Interactions David Levens, Erez Aiden, Laura Baranello, Konstantin Severinov

• Modeling DNA Topoisomerases and Topology Sarah Harris, Davide Marenduzz, Mariel Vasquez

• Topoisomerases and DNA Topology in Cancer Chemotherapy Scott Kaufmann, Mary-Ann Bjornsti, Junjie Chen, Karen Vasquez

• DNA Topology and Topoisomerases at the Single Molecule

Level Alice Pyne, Zev Bryant, Michelle Wang • Topoisomerases as Cellular Poisons and Essential

Enzymes Shunichi Takeda, Anna Bizard, Nayun Kim, Yuh-Hwa Wang • Topoisomerase Structure and Function Valerie Lamour,

Chairs: Anusha Pusuluri and Nicholas Lamson

Drug Metabolism Drug Discovery to Precision Therapeutics: Novel Mechanisms, Models and Technologies JUL 10-15, 2022 HOLDERNESS SCHOOL, HOLDERNESS, NH CHAIR: J. Steven Leeder VICE CHAIR: Jane Kenny

• Keynote Session: Integration of Drug Metabolism Science

and Big Data to Inform Precision Medicine Jane Kenny, Sir Munir Pirmohamed

• Drug Transporters: Advancing Drug Development and

Precision Therapeutics Andrew Goodman, Nichole Klatt, Matthew Redinbo, Peter Turnbaugh, Michael Zimmermann

• Drugs of the Future: Probing the ADME Properties of Novel

Therapeutics Sara Humphreys, Gaurav Bhardwaj, Diane Ramsden • Drug Metabolism by Intestinal Microorganisms Kim Brouwer, Bruno Hagenbuch, Kaspar Locher, Pallabi Mitra, Gauri Rao

• New Techniques in Drug Metabolism Methodology Katherine Elvira, Xiaomeng Shen, Boyang Zhang

• Prediction of Drug Metabolism In Vivo from In Vitro Studies Cyrus Khojasteh, Leslie Benet, Murat Cirit, Hiroyuki Mizuguchi, Charity Nofziger

• Selected Poster Presentations Patrick Murphy • Mechanisms of Drug Metabolism Emily Scott, Xinxin Ding, Ruili Huang, Eric Johnson, Richard Auchus

• Harnessing Technology to Advance Individualized

Therapeutics Namandje Bumpus, Netz Arroyo, Catherine Fenselau, Manthena Varma

Enzymology, Cellular Functions, Roles in Diseases and Therapeutic Targeting AUG 6-7, 2022 Chairs: Amanda Riccio and Thomas Germe

Mechanisms and Approaches to Overcoming Drug Resistance in Cancer, Infectious Disease and Agriculture JUN 25-26, 2022 CHAIR: Michael Lombardo

Drug Safety Advances in Models, New Modalities and Clinical Considerations for Drug Safety JUN 19-24, 2022 STONEHILL COLLEGE, EASTON, MA CHAIR: Myrtle Davis VICE CHAIR: Ruth Roberts

• Keynote Session: Modeling Complex Biological Systems David Watson, Dennis Discher

• Emerging Applications of Big Data and Machine Learning

in Safety Assessment James Stevens, Daniel Rudmann, Melissa Hallow, Laszlo Urban, Erio Barale-Thomas

• Leveraging Human Genetics and Big Data to Inform Drug

Safety Blanca Rodriguez, Danish Saleheen, Lucas Ward, Hao Zhu • Biomarker Science in Drug Discovery and

Development Vishal Vaidya, Guruprasad Aithal, Holly Soares • Microphysiological Models: Advances in Modeling

Complex In Vivo Functions and Organ Responses Anthony Bahinski, Kyle Kolaja, Mark Donowitz, Joanna Burdette, Girija Goyal

• New Paradigms in Translational Safety Science Leigh Ann Burns Naas, Lolke Dehaan, Gary Gilmour, Michael Morton, Eric Sobie

• Novel Therapeutic Modalities: Challenges and Opportunities

in Nonclinical Safety Assessment Strategies Wendy Freebern, Jeff Willy, Fiona Spence, Kathy Meyer, Padma Narayanan

• Full Utilization of the Clinical Experience in the Nonclinical

Space Michelle Berny-Lang, Kelly Filipski, Bonnie Ky, Christine Miaskowski, Yinghong Mimi Wang

• The GRC Power Hour™

• Keynote Session: Advancing Drug Safety Through Innovation

Drug Metabolism

• The GRC Power Hour™ Michelle Berny-Lang, Leigh Ann Burns Naas

James Berger, Nei-Li Chan

DNA Topoisomerases in Biology and Medicine

Drug Resistance

Ruth Roberts, Manasi Nandi

Translational Models and Technologies to Predict Drug Disposition and Response JUL 9-10, 2022 CHAIR: Chelsea Hosey

Drug Safety Emerging Technologies and Strategies for Drug Safety Evaluation JUN 18-19, 2022 CHAIRS: Lauren Lewis and Molly Morgan

Electron Donor-Acceptor Interactions Electron and Energy Transfer Processes: New Perspectives and Emerging Directions JUL 31-AUG 5, 2022 SALVE REGINA UNIVERSITY, NEWPORT, RI Chairs: Felix Castellano and Claudia Turro Vice Chairs: Lin Chen and Ferdinand Grozema

• Bio-Inspired Charge Transfer Chemistry Sherri McFarland, Leif Hammarstrom, Hannah Shafaat, Harry Gray

“

GRCs are such a positive experience. The conferences are relatively small and very informal. Meeting people and talking shop for a week is better than a vacation. J. ROBERT DURRWACHTER, Cambrex

”

• Spin Control of Electron Transfer Processes Malcolm Forbes, Natia Frank, Martin Kirk, Stephen Holmes, Danna Freedman

• Photoredox Driven Chemical Transformations James McCusker, Corey Stephenson, Carsten Milsmann, Oliver Reiser

• Photonic Materials Lea Nienhaus, Dan Congreve, Xiaosong Li, Nobuhiro Yanai, Justin Caram

• Molecular Charge Transfer Elena Galoppini, Mark Thompson, Gerald Meyer, Karen Mulfort

• Catalysis Towards Sustainable Fuels Etsuko Fujita, Clifford Kubiak, Jenny Yang, Elena Jakubikova, Alexander Miller

• Charge Transport in Complex Architectures and Interfaces Dirk Guldi, Cody Schlenker, Gemma Solomon

• Energy Transfer, Fusion and Fission David Shultz, Amanda Morris, Justin Johnson, Oliver Wenger, Ken Hanson

• Keynote Session: Coherence in Charge Transfer Processes Niels Damrauer, Gregory Scholes, Jeffrey Rack, Michael Wasielewski

• The GRC Power Hour™ Sherri McFarland, Amanda Morris

Electron Donor-Acceptor Interactions From Fundamentals to Applications in Energy Conversion and Beyond JUL 30-31, 2022 CHAIRS: Alexandria Bredar and Jacob Spies

The Confluence of Science- and Machine-Based Learning Approaches in Energetic Materials Research JUN 26-JUL 1, 2022 SOUTHERN NEW HAMPSHIRE UNIVERSITY, MANCHESTER, NH Chair: Joseph Zaug Vice Chair: Lori Groven

• From Atomic- to Micro-Scale Phenomena: Beginning at

Ignition Katharine Tibbetts, Lee Perry, Rebecca Lindsey, Joseph Olles • Meso-Scale Phenomena Illuminated by Science- and

Machine-Based Learning Santanu Chaudhuri, David Kittell, Paul Lafourcade, Oishik Sen

• Machine-Based Learning: Algorithms in Support of

Chemical Prescriptions Brian Barnes, Anna Hiszpanski, Koji Tsuda, Bartosz Grzybowski, Anshumali Shrivastava

• Materials Synthesis: Organic, Inorganic and In Silico Qian Yang, Olexandr Isayev, Virginia Manner, Sili Deng

• Advanced Manufacturing: Optimizing Performance by

Design Jena McCollum, Blair Brettmann, Yoav Eichen • Thermodynamics and Kinetics: Tailoring the Power of

Energetic Materials Matthew Kroonblawd, Sorin Bastea, Deanna Lacoste, Carole Morrison

• Thermal-Mechanical Dynamics: Learning from Emergent

Response Jesus Mares, Marisol Koslowski, Gary Seidel

Understanding Endothelial Cell Diversity: Regulation and Regenerative Potential

• Fireball Dynamics Michael Soo, Christopher Goldenstein, Jennifer

JUN 26-JUL 1, 2022

• The GRC Power Hour™ Deanna Lacoste

Victoria Bautch, Christer Betsholtz

• Molecular Regulation of Endothelial Phenotypes Karina

Joseph Kalman, Devon Swanson Gottfried, Mark Phillips

Ostergaard, Miikka Vikkula, Jason Fish, Susan Quaggin

• Endothelial Cell Damage, Repair and Regeneration Joyce Bischoff, Luisa Iruela-Arispe, Yoshiaki Kubota, Shahin Rafii

• Aging Endothelium and Impact on Disease Progression Eli Keshet, Jaime Grutzendler, Ebba Brakenhielm, Massimiliano Mazzone

• Hematovascular Interactions in Development and

Disease Christiana Ruhrberg, Stefania Nicoli, Kenneth Walsh, Taija Makinen • Advances in Vascular Imaging and Bioengineering Mary Dickinson, Friedemann Kiefer, Rui Benedito, Julien Vermot

• Vascular Metabolism Timothy Hla, Zoltan Arany, Mariona Graupera, Michael Potente, Michael Simons

• Emerging Approaches to Understanding Cellular Diversity

JUN 25-26, 2022 CHAIRS: Will Bassett and Matthew Kroonblawd

Innovative Science for the Grand Challenges in Aquatic Environmental Sciences JUN 19-24, 2022 HOLDERNESS SCHOOL, HOLDERNESS, NH CHAIR: Heileen Hsu-Kim VICE CHAIR: Thomas Hofstetter

• Biodegradable Polymers and Plastic

Contamination Michael Sander, Marc Hillmyer, Richard Gross • An Updated Look into (Waste) Water Treatment Processes Kyle Bibby, Michael Dodd, Peiying Hong, Krista Wigginton

• Environmental Metabolomics David Wishart, Pieter Dorrestein, Michael Zimmermann

• The Continuing Threat of Halogenated Contaminants Elizabeth Edwards, Frank Löffler, Carla Ng, Jinyong Liu

• The Increasing Complexity of Chemical Pollution:

New Avenues for Identifying Unknowns and Assessing Effects Beate Escher, Mingliang Fang, Emma Schymanski • New Chemistry and New Materials for Water Treatment Marta Hatzell, Christopher Gorski, T. Alan Hatton, Wendy Queen

• New Views on Contaminant Transformation Processes Thomas Borch, Huichun Zhang

• Environmental Biogeochemistry and Anthropogenic Impacts Desiree Plata, Asmeret Asefaw Berhe, Ulf Skyllberg, Lenny Winkel

• Aquatic Sciences at the Science-Policy Interface Rainer Lohmann, Laurel Schaider

• The GRC Power Hour™

JUN 18-19, 2022 CHAIRS: Imari Walker Karega and Adam Simpson

Environmental Endocrine Disruptors EDCs and the Environment JUN 19-24, 2022 JORDAN HOTEL AT SUNDAY RIVER, NEWRY, ME CHAIR: Jodi Flaws VICE CHAIRS: Juliette Legler and Angel Nadal

• Keynote Session: Environmental Endocrine Disrupting

Chemicals Angel Nadal, Bernard Robaire, Shanna Swan, Gail Prins • Evidence for an Mechanisms of EDC-Induced

Reproductive Toxicity Vasantha Padmanabhan, Patrick Hannon, Pauliina Damdimopoulou, Aileen Keating, Laura Vandenberg

• Impacts on the Brain and Behavior Andrea Gore, R. Thomas Zoeller, Heather Patisaul, Sakina Mhaouty-Kodja, Ramendra Saha

Risks from EDCs Laura Vandenberg, Kevin Elliott, Katie Boronow, Ami Zota, R. Thomas Zoeller

CHAIRS: Nicholas Chavkin and Gabriela D'Amico

Environmental Sciences: Water

Environmental Sciences: Water

• Social, Cultural, and Political Determinants of Evaluating

JUN 25-26, 2022

JUN 18-19, 2022

Investigating the Status of Water Quality, Technology and Distribution from Glacial Sources to Contaminated Runoff

• The GRC Power Hour™ Luisa Iruela-Arispe, Katie Bentley

Understanding Endothelial Cell Diversity: Regulation and Regenerative Potential

Environmental Endocrine Disruptors Harnessing Interdisciplinary Evidence for Endocrine Disruption to Improve Public Health

Physicochemical Processes in Reacting Energetic Materials from the Nano to Macro Scale

Katie Bentley, Kari Alitalo, Clint Miller, Bin Zhou, Holger Gerhardt

Endothelial Cell Phenotypes in Health and Disease

Rock, Nikki Posnack, Lindsey Treviño

• The GRC Power Hour™ Heather Patisaul, Laura Vandenberg

Energetic Materials

Yaniv, Martin Schwartz, Natasha Harvey, Mark Kahn, Anne Eichmann

• Congenital Defects and Clinical Therapy Gou Young Koh, Pia

Balance and Cellular Metabolism Almudena Veiga-Lopez, Kylie

CHAIRS: Kylie Rock and Genoa Warner

• Intelligently Designed Propellants Andrew Demko, Ralf Kaiser,

• Endothelial Cell Heterogeneity Hellmut Augustin, Ralf Adams,

Swan, Rita Strakovsky, Jennifer Adibi, Cynthia Curl, Tamarra James-Todd

• Effects of Environmental Endocrine Disruptors on Energy

Energetic Materials

Endothelial Cell Phenotypes in Health and Disease

REY DON JAIME GRAND HOTEL, CASTELLDEFELS, SPAIN CHAIR: Karen Hirschi VICE CHAIR: Christiana Ruhrberg

• EDC Effects in the Context of Human Exposure Shanna

• Emerging Exposures, Nonclassical Environmental

Endocrine Disruptors, and Safer Alternatives Genoa Warner, Thad Schug, Terrence Collins, Shuo Xiao, Bernard Robaire

• Short and Long-Term Consequences of Developmental

Exposure to EDCs Patrick Hannon, Marisa Bartolomei, Ramji Bhandari, Paola Palanza, Almudena Veiga-Lopez

• Environmental Endocrine Disruptors in the Marine and

Terrestrial Environment Juliette Legler, Ramji Bhandari, Ben Parrott, Turk Rhen

Enzymes, Coenzymes and Metabolic Pathways Enzyme Mechanisms with Applications to Metabolism, Epitranscriptomics and Drug Discovery JUL 24-29, 2022 WATERVILLE VALLEY, WATERVILLE VALLEY, NH CHAIRS: Andrew Murkin and Lynn Abell VICE CHAIRS: Satish Nair and Luiz Pedro Carvalho

• Enzymology in the Innate Immune System Heather Hundley, Peter Beal, Yorgo Modis, Manal Swairjo

• Enzyme Evolution and Engineering Nicholas Silvaggi, Tobias Erb, Donald Hilvert, Paola Laurino, David Sherman

• Enzymes Involved in Post-Translational Modifications Walter Fast, Sonja Lorenz, Minkui Luo, Paul Thompson

• Inhibitor Design Elham Behshad, Argyrides Argyrou, Andrew Bennet, Caren Freel Meyers

• Conformational Effects on Catalysis and Inhibition Patrick Frantom, James Fraser, Randy Kipp, John Richard

• Enzyme Kinetics in Complex Systems Dhara Shah, Swati Nagar, Matthew Robers, Bharath Srinivasan, Peter Tonge

• Enzyme Mechanisms Katherine Hicks, Squire Booker, Emily Parker, Timothy Wencewicz

• Methodological Advances for Studying Enzymes Audrey Lamb, Gabriel Lander, David Dulin, Denis Rousseau

• Perspectives on Modulation of Enzyme Activity Catherine Drennan, Carol Fierke, Paul Fitzpatrick

• The GRC Power Hour™ Lynn Abell

Enzymes, Coenzymes and Metabolic Pathways The Enzymology of Human Health, Biotechnology and the Environment JUL 23-24, 2022 CHAIR: Tyler Stack

Extracellular Vesicles

Flow and Transport in Permeable Media

The Dichotomy of EVs: From Biomarkers and Purveyors of Disease to Potential Therapeutic Agents

Active and Passive Transport Processes in Biological and Geophysical Flows

JUL 23-24, 2022

JUL 16-17, 2022

CHAIRS: Kilean Lucas and Kyle Mentkowski

CHAIRS: Amir Pahlavan and Rebecca Liyanage

Fibroblast Growth Factors in Development and Disease FGF Signaling: Understanding Function and Devising Therapeutic Tools

Epithelial Stem Cells and Niches Tissue Stem Cell Regulation by Autonomous and Non-Autonomous Mechanisms JUN 5-10, 2022 VENTURA BEACH MARRIOTT, VENTURA, CA Chairs: Michael Shen and Valerie Horsley Vice Chairs: Ophir Klein and Kim Jensen

• Tissue Stem Cell Function Samantha Morris, Nick Barker, Sarah

MAY 1-6, 2022 RENAISSANCE TUSCANY IL CIOCCO, LUCCA (BARGA), ITALY CHAIRS: Mohammad Hajihosseini and Mark Lewandoski VICE CHAIR: Amy Merrill

• Keynote Session: Early Development, Organogenesis and

Evolution David Ornitz, Suzanne Mansour, Didier Stainier • Musculoskeletal and Craniofacial Roles Amy Merrill, Marja Hurley, Timothy Saunders, David Ornitz, Andrew Wilkie

• Interaction of FGFs with Other Signaling Pathways Saverio

Knox, Emi Nishimura

• Niche Interactions Anjelica Gonzalez, Carla Kim, Pantelis Rompolas • New Models and Technologies Pantelis Rompolas, Fernando Camargo, Samantha Morris

• Bioengineering of Stem Cells and Niches Rongwen Xi, Anjelica Gonzalez, Michael Longaker, Sara Wickstrom

• Regulation of Stem Cell Differentiation Shruti Naik, Ya-chieh Hsu, Rongwen Xi

Bellusci, Joshua Brickman, Igor Stagljar

• Stem Cells, Tissue Regeneration and Repair Joshua Brickman, Denise Al Alam, Sabine Werner, Saverio Bellusci, Helen Makarenkova

• Structural Biology of FGFs and Novel Technologies Denise Al Alam, Chiara Francavilla, Moosa Mohammadi

• FGFs in Cancer: Mechanism, Progression and Therapy Fernanda Laezza, Richard Grose, Florian Siebzehnrubl, Fen Wang

• Stem Cell Plasticity in Development and Cancer Fernando Camargo, Cedric Blanpain, Aaron Zorn

• Immune Microenvironment Sara Wickstrom, Judith Agudo, Calvin Kuo, Shruti Naik

• Metabolic Homeostasis and Endocrine Functions Sabine Werner, Jarrad Scarlett, Carmine Settembre

• FGFs in Development and Disease of the Nervous System Suzanne Mansour, Martin Berghoff, Xin Zhang, Hiroshi Kawasaki

• Niche Dysregulation in Disease and Cancer Ya-chieh Hsu, Wouter Karthaus, Mark Krasnow, Ilaria Malanchi

• Intracellular-Acting and Non-Canonical FGFs Marja Hurley,

• The GRC Power Hour

™

Epithelium Dynamics During Development, Regeneration, Disease and Aging

Extracellular Vesicles Understanding Extracellular Vesicle Biogenesis and Composition for Detection and Treatment of Diseases JUL 24-29, 2022 GRAND SUMMIT HOTEL AT SUNDAY RIVER, NEWRY, ME CHAIRS: Paul Robbins and Kenneth Witwer VICE CHAIRS: Esther Nolte-'t Hoen and Edit Buzas

• Keynote Session: Physiologic and Pathologic Roles of EVs Edit Buzas, Clotilde Théry, David Lyden

• Biogenesis and Composition of EVs Clotilde Théry, Deborah Goberdhan, Stanley Lemon, Crislyn D'Souza-Schorey, Anthony Ferrante

• New Technologies for Quantitating and Analyzing EVs Adrian Morelli, Louise Laurent, Shannon Stott, Juan Falcon-Perez

• Role of Endogenous EVs in Driving Disease

Pathology David Lyden, Andrew Hill, Lucia Languino, Dolores Di Vizio, Jacky Goetz

• EVs as Delivery Vehicles for Drugs and RNAs Andrew Hill, Pieter Vader, Charles Lai

• Novel Therapeutic Applications of EVs Jacqueline Bromberg, Adrian Morelli, Bharat Ramratnam

• EVs in Host-Pathogen Interactions Esther Nolte-'t Hoen, Ana Torrecilhas, Arne Weiberg, Jeff Schorey, Navneet Dhillon

• Stem Cell EVs for Regenerative Medicine Anastasia Khvorova, Susmita Sahoo, Sai Kiang Lim, Benedetta Bussolati, Ewa Zuba-Surma

• Current Clinical Trials with EVs Sai Kiang Lim, Maria Brizzi, Eva Rohde

• The GRC Power Hour™ Edit Buzas

• Keynote Session: Forensic Applications of New Genetic

and Biomedical Technologies Pamela King, Christopher Mason • Haploid and Alternate Autosomal Markers Rebecca Just, Arwin Ralf, Daniele Podini

• Forensic Genetic Genealogy: Inferring Identity with

Long-Range Familial Searches Thomas Callaghan, Fred Bieber, Debbie Kennett

• Activity Level Research and Impact on Forensic Reporting Duncan Taylor, Laurence Devesse, Roland van Oorschot, Lydie Samie-Foucart

• Tissue Source Attribution: Epigenetic, microRNA and

mRNA Approaches to Attribution Robin Cotton, Cordula Haas, Hwan Lee

• Age, Ancestry and Appearance Prediction Denise Syndercombe Court, Lutz Roewer, Susan Walsh, Runa Daniel

• Proteomic, Methylomic and Microbiomics Sally Harbison, Glendon Parker, Zachary Goecker, Athina Vidaki, Baneshwar Singh

• Bioinformatics and Data Science Christopher Phillips, Rolf Ypma, Noah Rosenberg, Ellen Greytak

Fibroblast Growth Factors in Development and Disease

• The GRC Power Hour™ Katherine Gettings

APR 30-MAY 1, 2022 C HAIRS: Kel Vin Woo and Theresa Rauschendorfer

DNA Analysis Charlotte Word, Tiffany Layne, Melissa Taylor, David Kaye, Paul Speaker

Forensic Analysis of Human DNA New Methods for Human Identification and Investigative Intelligence JUN 18-19, 2022

JUN 4-5, 2022 CHAIRS: Francesco Cambuli and David Castillo-Azofeifa

JUN 19-24, 2022 MOUNT SNOW, WEST DOVER, VT Chairs: Sarah Seashols Williams and Steven Lee Vice Chairs: Katherine Gettings and Titia Sijen

Fernanda Laezza, Geoffrey Pitt

Biology, Technology and Translation in FGF Research

Epithelial Stem Cells and Niches

Leveraging Human Diversity, Data Science and Marker Discovery to Shape Future Forensic Applications

• Addressing Human Factors and Cognitive Bias in Forensic

• Keynote Session: Stem Cells, Niches, and Cancer Cedric Blanpain, Fiona Watt, Leonard Zon

Forensic Analysis of Human DNA

Flow and Transport in Permeable Media Interactions Between Fluids, Elements, Materials, Energy and Life in Porous and Fractured Media JUL 17-22, 2022 LES DIABLERETS CONFERENCE CENTER, LES DIABLERETS, SWITZERLAND CHAIR: Tanguy Le Borgne VICE CHAIR: Marc Hesse

• Dynamics of Carbon Dioxide in the Subsurface Martin Blunt, Sam Krevor, Benedicte Menez

• Impact of Fluid and Solid Deformation on Transport and

Mixing Marco Dentz, Daniel Lester, Chris MacMinn, Andrew Clarke • Controls of Subsurface Flow and Transport on Earth's

Hydrological and Geochemical Cycles Ilenia Battiato, Kate Maher, James Kirchner

• Pore Scale Physics of Multiphase and Complex Flows Steffen Berg, Ryan Armstrong, Marcio Carvalho, Alex Hansen

• Fluid Mechanics of Droplets and Bacteria Dani Or, François Gallaire, Yohan Davit

• Coupled Flow and Transport in Ice and Planetary Systems Jerome Neufeld, Kenneth Golden, Christine McCarthy, Christophe Sotin

• Non-Invasive Methods and Data Assimilation Strategies

for Exploring Subsurface Processes Stig Niklas Linde, Haruko Wainwright, Lee Slater

• Fractures, Hydromechanics and Seismicity Ruben Juanes, Marie Violay, François Renard, Robert Viesca

• Soil Processes from Micro to Continental Scales Insa Neuweiler, Asmeret Asefaw Berhe, John Selker

• The GRC Power Hour™

CHAIRS: Tiffany Layne and Laurence Devesse

Fragile X and Autism-Related Disorders Novel Technologies to Advance Discovery of Disease Mechanisms and Therapeutics for Fragile X and Autism MAY 15-20, 2022 RENAISSANCE TUSCANY IL CIOCCO, LUCCA (BARGA), ITALY CHAIR: Mustafa Sahin VICE CHAIR: Kimberly Huber

• Keynote Session: From Genes to Drugs in

Neurodevelopmental Disorders Kimberly Huber, Evdokia Anagnostou, Peter Kind, Tracy King

• Genetic Heterogeneity Alice Luo Clayton, Catalina Betancur, Jacquemont Jacquemont, Joel Richter

• Convergence of Molecular Mechanisms Jennifer Darnell, Nicola Allen, Barbara Bardoni, Helen Bateup

• Human Cellular Models Laura Mamounas, Robin Kleiman, Xinyu Zhao • Circuit Biology in Animal Models Emily Osterweil, Andreas Frick, Peter Tsai, Zhaolan (Joe) Zhou

• Human Physiology and Biomarkers Thomas Frazier, Lauren Ethridge, Shafali Jeste, Charles Nelson

• Mechanisms and Therapies for Syndromic Autism Michael Tranfaglia, Michela Fagiolini, Mark Zylka, Brielle Ferguson

• Novel Model Systems and Platforms Claudia Bagni, David Hampson, Devin Binder, Gul Dolen

• Innovative Approaches to Clinical Outcome Measures and

Trial Design Elizabeth Berry-Kravis, Randi Hagerman, Michelle Krishnan

• The GRC Power Hour™ Elizabeth Berry-Kravis, Emily Osterweil

Fragile X and Autism-Related Disorders

Genetic Biocontrol

Lessons From Differences and Similarities in FXS and Other ASDs

New Biological Platforms for Affecting Phenotype Changes for Control

MAY 14-15, 2022

JUN 26-JUL 1, 2022 FOUR POINTS SHERATON, HOLIDAY INN EXPRESS, VENTURA, CA CHAIRS: David O'Brochta and Alfred Handler VICE CHAIR: Omar Akbari

CHAIRS: Sophie Thomson and Elizabeth McCullagh

Frontal Cortex

NEW!

Frontal Cortex Structure and Function Across Model Systems AUG 7-12, 2022 VENTURA BEACH MARRIOTT, VENTURA, CA CHAIRS: Mark Laubach and Alicia Izquierdo VICE CHAIRS: Rebecca Shansky and David Moorman

• Functional Topography of the Frontal Cortex Across

Species Mark Baxter, Celine Amiez, Sarah Heilbronner • Sex Differences in Structure and Function Rebecca Shansky, Heather Brenhouse, Mohammed Milad, Cara Wellman

• Insights into Frontal Cortex Function from Neural

Recordings Matthew Roesch, Nancy Padilla-Coreano, Erin Rich, Jeremy Seamans

• Frontal Circuits in Learning and Decision Making Peter Rudebeck, Laura Bradfield, Arif Hamid, Joni Wallis

• Aversive Processing and the Impact of Chronic Stress Bita Moghaddam, Shannon Gourley, Dean Mobbs, Maria Diehl

• Reward Processing Christopher Lapish, Xinying Cai, Christine Constantinople, Gorica Petrovich

• Frontal Cortex in Substance Use James Jentsch, Kathleen Grant, Bruce Hope, Ryan LaLumiere

• Frontal Cortex and Executive Functions Yogita Chudasama, Verity Brown, Nicola Grissom, Mehdi Khamassi

NEW!

• Keynote Session: Operationalizing Genetic Biocontrol Omar Akbari, Kostas Bourtzis, Scott O'Neill, Andrea Crisanti

• Inducing and Programming Sterility and Lethality for

Genetic Biocontrol Marc Schetetig, Givemore Muhenga, Pablo Liedo, Kevin Gorman, Maxwell Scott

• Mechanisms and Applications of Natural and Engineered

Genetic Incompatibilities Jeremy Herren, Michaei Smanski, Zhiyong Xi

• Manipulating Microbiomes to Affect Host Phenotypes Kostas Bourtzis, George Dimopoulos, Jeremy Herren, Grant Hughes, Brian Weiss

• Social and Regulatory Science as Enablers of Genetic

Biological Control Stephanie James, Brinda Dass, Abdoulaye Diabate, Willy Tonui, Camilla Beech

Narayanan, Angela Roberts

• The GRC Power Hour™

Fuel Cells Integrating Theory, Synthesis, Characterization and Validation for the Advancement of Fuel Cell Research JUL 24-29, 2022 BRYANT UNIVERSITY, SMITHFIELD, RI CHAIRS: Marc Secanell and Shanna Knights VICE CHAIRS: Iryna Zenyuk and Vojislav Stamenkovic

• A Global Perspective on Fuel Cell Development Jonathan Sharman, Siyu Ye, Rod Borup

• Novel Oxygen Reduction Reaction Catalysts Plamen Atanassov, Lior Elbaz, Arunima Singh

• Characterizing Catalyst Activity Yu Morimoto, Kateryna Artyushkova, Anthony Kucernak

• Designing Better Solid Electrolytes Steven Holdcroft, Wen Liu, Yushan Yan, Stephen Paddison

• Novel Membrane Fabrication Approaches Göran Lindbergh, Simon Thiele, Marcelo Lozada-Hidalgo

• Understanding Material-Structure-Performance Interactions

in Fuel Cell Electrodes Kensaku Kodama, Adam Weber, Jeff Gostick, Paulo Ferreira

• Technologies for a Hydrogen Economy Huyen Dinh, Thomas Jaramillo, Nemanja Danilovic

• Understanding Reactant Transport and Cell Durability Jasna Jankovic, Hubert Gasteiger, Marc-Olivier Coppens, Felix Buchi

• Advances in Polymer Electrolyte Fuel Cell Design Thomas Zawodzinski, Shimshon Gottesfeld

• The GRC Power Hour™ Shanna Knights

Fuel Cells Fuel Cells: From Fundamental Electrochemistry to Engineering Applied Materials JUL 23-24, 2022 CHAIRS: Sadia Kabir and Mayank Sabharwal

Shawn Hood

• Geochemistry and Fundamental Mineral-System-Forming

Processes John Dilles, Constantino Mpodozis, Madeleine Humphreys, Santiago Tassara, Nicholas Hayward

• Next Generation Models Koen Torremans, Juan Carlos Afonso, Stefan Luth

• Geochemical Processes Contributory to Superior-Grade

Development Elizabeth Holley, Katie McFall, Brian Tattich, Alex Gysi, Andrew Wurst

• Mining Frontiers Danielle Schmandt, Melissa Anderson, Abigail Calzada-Diaz

• Geochemistry for Discovery Christian Ihlenfeld, Michael Whitbread, Iain Dalrymple, Amanda Stoltze, Simon Griffiths

• Biological Processes and Ore Deposits Sylvia Sander, Donato Giovannelli, Gordon Southam

• Geochemistry in Value Realization and Stewardship Kathy Ehrig, Karin Olson Hoal, David Barrie Johnson, Siobhan Wilson, Evelyn Mervine

• The Future of Geochemistry of Mineral Deposits Natalie Caciagli, John Thompson

• The GRC Power Hour™

• Manipulating Sex Determination to Affect Genetic

Biocontrol Maxwell Scott, Philippos Papathanos, Godana Rašic, Jake Tu, Giuseppe Saccone

• Soft and Hard Technologies to Enable Genetic Biocontrol Jake Tu, Anna Buchman, Ruth Müller, Jason Rasgon, Ernst Wimmer

• Gene Drive Genetics and Genetic Engineering Ernst Wimmer, Luke Alphey, Anthony James, Paul Thomas

• Mathematical Modelling for Successful Genetic Biocontrol John Marshall, Florence Debarre, Fred Gould, Kim Pepin, Toni Piaggio

• The GRC Power Hour™

• Keynote Session: Frontal Dysfunction in Psychiatric

Disease David Kupferschmidt, Laura DeNardo, Nandakumar

• Big Data and Mineral Deposits John Vann, Shaunna Morrison,

Genomic Instability Genomic Instability, DNA Repair and Human Diseases JUL 10-15, 2022 FOUR POINTS SHERATON, HOLIDAY INN EXPRESS, VENTURA, CA CHAIRS: Lee Zou and Michael Huen VICE CHAIRS: Agata Smogorzewska and Kyungjae Myung

• Keynote Session: Genetics and Genomics on Genome

Instability J. Ross Chapman, Andre Nussenzweig, Roger Greenberg • Repair of Chromosome Breaks Travis White, Patrick Sung, Stephen Kowalczykowski, Maria Jasin, Tanya Paull

• Genomic Instability and DNA Repair During the Cell

Cycle Qing Li, Stephen West, Larraine Symington, Hongtao Yu • DNA Replication and Replication Stress Shan Zha, Orlando Schärer, Anindya Dutta, Bik Tye, Xiaolan Zhao

• Transcription, R-Loops and DNA Repair Chetan Rawal, Gaelle Legube, Li Lan, Dana Branzei, Lei Li

• Chromatin Dynamics and Epigenetic Regulation of DNA

Repair Evi Soutoglou, Qing Li, Kyle Miller, Jun Huang, Jessica Downs • Emerging DNA Repair Pathways Kyle Miller, Niels Mailand, Evi Soutoglou, Zhenkun Lou, Kyungjae Myung

• DNA Repair Defects and Diseases Li Lan, Shan Zha, Robert Weiss, Yosef Shiloh, Agata Smogorzewska, J. Ross Chapman

• DNA Repair Defects and Cancer Therapy Justin Wai Chung

Geochemistry of Mineral Deposits Geochemical Frontiers, Critical Processes and Value Creation MAY 21-22, 2022 CHAIRS: Philip Rieger and Irene del Real Contreras

Graft Preservation in Heart Transplantation

NEW!

Prolonged Heart Preservation: The Road From Organ Transport Toward Organ Banks JUL 17-22, 2022 VENTURA BEACH MARRIOTT, VENTURA, CA CHAIRS: Robert Bartlett and Cristiano Amarelli VICE CHAIR: Andreas Zuckermann

• A Disrupting Technology Jamshid Karimov, Johan Nilsson, Judith Arcidiacono

• DCD Donation and Ex-Situ Perfusion Carmelo Milano, Stephen Large, Kumud Dhital, Hendrik Tevaearai

• Ex-Situ Perfusion Over 24 Hours Bart Meyns, Benjamin Kappler, Alvaro Rojas-Pena

• Reconditioning the Failing Donor Grafts Luciano Potena, Kiran Kush, Arne Neyrinck, Alex Manara

• Regenerative Medicine Applied to Perfused Grafts Sandra Lindstedt, Dawn Bowles, James Mc Cully

• Immunoregulation and Regenerative Medicine Applied to

Machine Perfusion Martin Hoogduijn, Christine Falk, Darren Freed • Ex-Situ Perfusion of Abdominal Organs: Lessons From

Under the Diaphragm Gabriel Oniscu, Rutger Ploeg, Peter Friend • The Race Toward Organ Banks Josef Stehlik, Shaf Keshavjee, Davide D'Alessandro, Hannah Valantine

• Ex-Situ Perfusion and New Storage Solutions Sebastian Giwa, David McGiffin, Marcus Granegger

• The GRC Power Hour™ Kiran Kush

Leung, Junjie Chen, Xiaochun Yu, Binghui Shen

• The GRC Power Hour™

Genomic Instability The Influence of Chromosome Architecture and Cell Cycle on Repair and Maintenance of the Genome JUL 9-10, 2022 CHAIRS: Travis White and Chetan Rawal

Granular Matter Particulate Systems Across Scales: From Colloidal Science to Geophysics JUN 26-JUL 1, 2022 STONEHILL COLLEGE, EASTON, MA CHAIRS: Xiang Cheng and Nathalie Vriend VICE CHAIRS: Kimberly Hill and Joshua Dijksman

• Granular Matter in Industrial Processes Paul Mort, Jeremy Lechman, Marty Murtagh

Geochemistry of Mineral Deposits

• Active Suspensions Daphne Klotsa, John Brady, Rajesh Ganapathy,

Geochemical Frontiers, Critical Processes and Value Formation

• Jamming and Glass Transition Eric Corwin, Eric De Giuli,

MAY 22-27, 2022 REY DON JAIME GRAND HOTEL, CASTELLDEFELS, SPAIN CHAIRS: Sarah Gleeson and David Braxton VICE CHAIR: Isabelle Chambefort

Petia Vlahovska Jeffrey Morris

• Dynamics and Structures of Granular Flows JC Tsai, Nathan Keim, Kerstin Nordstrom, Yujie Wang

• Impact and Cratering German Varas, Hiroaki Katsuragi, Devaraj Van Der Meer

• Discrete and Continuum Mechanics Ted Brzinski, Karen Daniels, Ken Kamrin, Prabhu Nott

• Geophysical Granular Flow Gert Lube, Emily Brodsky, Chris

• Bleeding and Clotting Control Sanjana Dayal, Colin Kretz, Weikai Li, Lindsey George, Walter Kahr, Christopher Ng

• Keynote Session: Von Willebrand Factor and Kindlins in

Bleeding Disorders Gary Gilbert, Robert Montgomery, Edward Plow • The GRC Power Hour™ Gow Arepally, A. Valance Washington

Catherine O'Sullivan, Kenichi Soga, Gordon Zhou

• Cohesion Between Generations of Granular Matter

Researchers Cacey Bester, Olivier Pouliquen

Regulation and Molecular Dynamics of Hemostasis and Thrombosis JUL 30-31, 2022 CHAIRS: Amy Siebert-McKenzie and Xu Han

JUN 25-26, 2022 CHAIRS: Ishan Srivastava and Jennifer Rieser

Green Chemistry Chemical Sciences Driving Sustainability JUL 24-29, 2022 REY DON JAIME GRAND HOTEL, CASTELLDEFELS, SPAIN CHAIRS: Walter Leitner and Emilio Bunel VICE CHAIRS: Audrey Moores and Jinlong Gong

• Keynote Session: A Systems Approach to Green Chemistry Steve Howdle, Paul Anastas, Peter Seeberger, Elsje Alessandra Quadrelli

• Harvesting Renewable Energy with Green Chemistry

Heterocyclic Compounds

• Hypothalamus and Complex Social and Inter-Species

• Strategic Approaches to the Preparation of Heterocyclic

Natural Products Wei Li, Ang Li, Margaret Brimble • New Approaches to Heterocyclic Compound Construction Sudeshna Roy, Larry Yet, Lee Silverberg, Edward Salaski, Shanina Johnson

• Design and Synthesis of Biologically Active Heterocycles Carmela Molinaro, Brian Aquila, Stephen Greszler, Donn Wishka

• Catalytic Methods for Heterocyclic Compound Preparation and

• Valorization of Waste Material Heriberto Cabezas, Adam Best, Jean-Paul Lange, Timo Repo

• Molecular Principles and Synthetic Applications Carmen Claver, Mika Tamas, Paul Chirik, Mimi Hii, Aiwen Lei, Hassan Bazzi, Eva Hevia

• Advanced Materials Buxing Han, Bruno Chaudret, Seth Darling • Environmentally Benign Synthesis, Processes and

Products Martina Peters, Christophe Darcel, Jason Tedrow, Karen

James Beck, Oliver Kappe, Kevin Moeller

Functionalization Eric Voight, Todd Hyster, Tanja Gulder, Helene Lebel • New Reaction Strategies for Heterocyclic Compound Design Jeffrey Gustafson, Tomas Smejkal, Carmela Molinaro, Thomas Stevenson

• Total Synthesis of Heterocyclic Natural Products Matthew

Industrial Processes R. Tom Baker, Philip Jessop, Avelino Corma • The GRC Power Hour™ Karen Goldberg

Green Chemistry Mapping Green Paths to Critical Elements, Molecules and Materials JUL 23-24, 2022 CHAIRS: Ana Patricia Pacheco and Amit Kumar

Pharmaceutical Relevance David Lathbury, Aaron Sather, Phillip Inglesby, Austin Smith, Maryll Geherty

• Keynote Session: Construction of Complex Molecular

Architectures Daniel Elbaum, Peter Wipf, Barry Trost • The GRC Power Hour™ Catharine Larsen, Sudeshna Roy

Human Genetic Variation and Disease Deciphering Genetic Complexity: Risk Assessment and Treatment Opportunities JUN 5-10, 2022 SOUTHERN NEW HAMPSHIRE UNIVERSITY, MANCHESTER, NH CHAIRS: Yana Bromberg and Olivier Lichtarge VICE CHAIRS: Hannah Carter and Kai Tan

• Keynote Session: Exploring Genome Perturbations in

Hemostasis Structure, Biochemistry and Physiology of Hemostasis JUL 31-AUG 5, 2022 WATERVILLE VALLEY, WATERVILLE VALLEY, NH CHAIRS: Sidney Whiteheart and Alan Mast VICE CHAIR: Gow Arepally

• Coagulation: Signaling and Structure Sriram Krishnaswamy, JoAnn Trejo, Jonas Emsley, Björn Dahlbäck

• Coagulation and Platelets Edward Conway, Martha Sola-Visner, Justin Hamilton, Nicola Mutch, A. Valance Washington, Zhenyu Li

• Maintaining Hemostatic Balance William Hobbs, Marie-Christine Bouton, Huanghe Yang, A. Koneti Rao

• Endothelium and Clotting Heyu Ni, John Hwa, Courtney Griffin, Mark Kahn, Jim Crawley, Audrey Cleuren

• Lessons of Molecular Hemostasis from Organisms that

Feed on Blood Joshua Muia, Mettine Bos, Ivo Francischetti, Diana Imhof

• Coagulation and Platelets in Diseases Ulhas Naik, Gustaf Edgren, Jill Johnsen, Sidney Strickland, Alisa Wolberg, Aaron Petrey

• Late-Breaking Topics Gow Arepally

Molecules to Sophisticated Behaviors Charles Bourque, Seth Blackshaw, Catherine Dulac

Behavior Nirao Shah, Annegret Falkner, Susana Lima, Xiaohong Xu • Hypothalamic Plasticity Zheng Li, Jaideep Bains, Marcelo Dietrich • Hypothalamus and Ingestive Behavior Garret Stuber, Amber Alhadeff, Lisa Beutler, Yuki Oka

• Rhythms in the Hypothalamus Luis De Lecea, Elena Gracheva, David Prober

• Hypothalamic Development, Cell Type Taxonomy and

Architecture Larry Swanson, Tibor Harkany, Deborah Kurrasch, John Campbell

• Hypothalamic Dysfunction Clifford Saper, Gul Dolen, Giles Yeo • The Neuroendocrine Hypothalamus Holly Ingraham, Christian Broberger, Stephanie Correa, Jenna McHenry

• The Hypothalamus and the Brain-Body Interface Sabrina Diano, Diego Bohorquez, Jeremy Borniger

• The GRC Power Hour™

Cook, Dennis Wright, Tomas Hudlicky

• Route Optimization of Heterocyclic Compounds of

Edler

• Keynote Session: From Mechanistic Understanding to

JUL 24-29, 2022 VENTURA BEACH MARRIOTT, VENTURA, CA CHAIRS: Michael Krashes and Dayu Lin VICE CHAIRS: Matt Carter and Alexander Jackson

JUN 19-24, 2022 SALVE REGINA UNIVERSITY, NEWPORT, RI CHAIR: R. Jason Herr VICE CHAIR: Catharine Larsen

• Designing Greener Products Deryn Fogg, Christoph Guertler, Silvia

Yonas Chebude, David Contreras, Mahdi Abu-Omar, Francois Jerome, Thomas Schaub

NEW!

Unraveling the Complexity of the Hypothalamus from Single Molecules to Intricate Behaviors

• Keynote Session: The Hypothalamus From Individual

• Paradigm Shifting Synthesis Technologies Kevin Frankowski,

• Chemical Value Chains Based on Biomass and CO2

Hypothalamus

Design, Synthesis and Application of Biologically Active Heterocycles

Marcella Bonchio, John Hansen, Greta Patzke, Yogesh Surendranath, Gonzalo Prieto Vignolini, Jakub Kostal

JUN 4-5, 2022

Hemostasis

Granular Matter Particulate Systems Across Scales: From Colloidal Science to Geophysical Flows

Building Bridges: From Variation Identification to Interpretation and Implementation CHAIRS: Anh-Thu Lam and Timothy Bergquist

Johnson

• Granular Geotechnical Engineering Elisabeth Bowman,

Human Genetic Variation and Disease

Health and Disease Graham McVicker, Jean-Laurent Casanova, Adam Godzik

• Genome Variation and COVID-19 Benjamin Greenbaum, Dennis Ko, Dmitry Korkin, Brent Richards, Judith Blake

• Host Genome and Microbiome Interactions Angela Poole, Emily Davenport, Alexandra Zhernakova

• Variants in Development and Early Onset Disease Gary

Image Science Emerging Imaging Techniques at the Intersection of Physics and Data Science JUN 5-10, 2022 GRAND SUMMIT HOTEL AT SUNDAY RIVER, NEWRY, ME CHAIR: Rafael Piestun VICE CHAIR: Jannick Rolland

• Information Extraction via Computational Imaging Matthew Kupinski, Roarke Horstmeyer, Sjoerd Stallinga

• Quantum Imaging George Barbastathis, Dan Oron, Nick Vamivakas • Artificial Intelligence in Image Science Chris Dainty, George Barbastathis, Aydogan Ozcan

• Multimodal and Biomedical Imaging Kyle Myers, Sophie Brasselet, Amy Oldenburg, David Sampson

• Inverse Problems in Imaging Richard Paxman, Mini Das, Demetri Psaltis

• Imaging in Emerging Consumer Applications Joyce Farrel, Kaan Aksit

• Astronomical and Space Imaging Thomas Bifano, Jeff Khun, Meredith Kupinski

• Eyes and Vision Jannick Rolland, Kristina Irsch, Hakan Ürey, Brian Wandell • Novel Lensless Imaging Sophie Brasselet, Laura Waller • The GRC Power Hour™

Hon, Elizabeth Bhoj, Steven Brenner, Wendy Chung, Lucia Peixoto

• Human Diversity and Disease Valerie Arboleda, Neil Hanchard

Image Science

• Cancer Genomics Kuan-lin Huang, Rachel Karchin, Anna

Image Acquisition, Processing and Visualization

Panchenko, Mona Singh, Itai Yanai

• Computational Interpretation of Variants in the Clinical

JUN 4-5, 2022 CHAIRS: Raman Saggu and Dennis Gardner

Context Constantina Bakolitsa, Sean Mooney, Marylyn Ritchie • Genome Variation and Disease Laura Conlin, Douglas Fowler, Martin Kircher, Predrag Radivojac, Janet Thornton

• Precision Medicine and Genomic Privacy Gamze Gursoy, Yves Moreau, Lucila Ohno-Machado

• The GRC Power Hour™ Anna Panchenko, Rachel Karchin

Immunochemistry and Immunobiology Immune System in Health, Disease and Therapy JUN 5-10, 2022 REY DON JAIME GRAND HOTEL, CASTELLDEFELS, SPAIN CHAIR: Facundo Batista VICE CHAIR: Alexander Rudensky

• Keynote Session: Immune Responses Alexander Rudensky, Jason Cyster, Gillian Griffiths

• Immunometabolism of the Tumor Microenvironment Brent Hanks, Juan Cubillos-Ruiz, Ming Li, Weiping Zou

• Immune Cells Trafficking and Activation Jason Cyster, Matteo Iannacone, Ronald Germain, Hai Qi, Michael Sixt, Gabriel Victora

• Gene Programming of Immune Cells Hai Qi, Alison Ringel, Thomas Boehm, Laura Mackay, Gioacchino Natoli, Nir Yosef

Maduke, Charles Caskey, Emad Ebbini

• Metabolism in Host Defense Sebastian Riquelme, Julie Magarian

• Emerging Opportunities for Intervening Upon

Immunometabolism in Disease Ana Mora, Ed Driggers, Richard

Becher, Ken Murphy, Jamie Spangler

• Immune Responses to Vaccine and Infection Carola Vinuesa, Matteo Iannacone, Antonio Lanzavecchia, Federica Sallusto

Siegel, Bruce Blazar

Douglas Kwon, Dan Littman Andrea Schietinger, Greg Barton, Sun Hur, Carla Rothlin

• Integrative Immunology Dan Littman, Carla Rothlin, Ana Domingos, Asya Rolls, Carola Vinuesa

• Tumor Immunity Asya Rolls, Jamie Spangler, Morgan Huse, Alison Ringel, Andrea Schietinger

JUN 12-17, 2022 GRAND SUMMIT HOTEL AT SUNDAY RIVER, NEWRY, ME CHAIR: Anu Ramaswami VICE CHAIR: Ming Xu

In Vivo Magnetic Resonance

• Frontiers of Industrial Ecology to Inform Sustainable

Identifying the Next 20 Years of Need in In Vivo MR JUL 17-22, 2022 PROCTOR ACADEMY, ANDOVER, NH CHAIR: Jeff Dunn VICE CHAIR: Kim Butts Pauly

and Conundrums Nabil Nasr, Raimund Bleischwitz, Hervé Corvellec • Advances in Methods: Circular Flows and Life Cycle

Assessment Tomer Fishman, Arnold Tukker, Shweta Singh, Stefan

Breakthroughs in New Research Areas Michael Smith,

Gara Villalba Mendez

• Engineering the Future of Magnetic Resonance

Technology Andrew Webb, Clarissa Cooley, Jan Korvink, Christoph

JUN 4-5, 2022

• Multimodal MRI: New Data from New

• Circular Economy: Food and the Food-Energy-Water Nexus

Combinations Sharmila Majumdar, Blaise Frederick, Vesna Sossi

Immunoengineering

NEW!

Immunomodulation Based on Cells, Therapies and Microenvironments

• Embracing Machine Learning and Graphics for MR

Processing and Visualization Cornelia Laule, Nicole Seiberlich, Valentina Pedoia Blackband, Samuel Grant, Klaus Scheffler

Resonance Elaine Bearer, Helene Benveniste, Youssef Zaim Wadghiri, Catherine Lebel

Health Susan Thomas, Madhav Dhodapkar, Kathrin Jansen, Darrell Irvine, Melody Swartz

• Magnetic Resonance for Visualizing the Unusual: MSK

from Equine to Mixed Reality Joel Garbow, Sarah Pownder, Brian Hargreaves

• Growth Areas in Immunology: Human Immunity Onyinye Iweala, Mark Davis, Bana Jabri, Marco Colonna

• Methods and Sequences for Acquiring Magnetic Resonance

Data Jurgen Hennig, Moritz Zaiss, Claudia Prieto, Jan-Bernd Hovener

• Systems and Computational Immunology Kathryn

• MRI for Space Research and Medicine Daniel Sodickson,

Miller-Jensen, Christina Leslie Janine Schuurman, George Georgiou, Mariana Kaplan

• In Vitro Models of Immunity Hyun Jung Kim, Britta Engelhardt, Linda Griffith

• Biomaterials for Vaccines and Immunomodulation Jamal Lewis, Martin Bachmann, Ed Botchwey, Suzie Pun, David Mooney

• Enabling Micro-Technologies to Assess Immune Cell

Function Armon Sharei, Daniel Irimia, Junsang Doh

• The GRC Power Hour™ Melissa Haskell, Kim Butts Pauly

Elias Ayuk, Ligy Philip, Zhiyong Jason Ren

• The GRC Power Hour™ Ming Xu, Callie Babbitt

Industrial Ecology Turning Research into Practice: Complexities of Industrial Ecology Implementation JUN 11-12, 2022 CHAIRS: Joe Bozeman III and Alexandra Westin

Identifying the Next 20 Years of Need in In Vivo MR

• Transformative Tools: Spatially Resolved Analysis for

Immunology Pamela Chang, Deborah Fowell, Garry Nolan • The GRC Power Hour™

NEW!

Basic and Translational Cellular Metabolism in Immunity JUN 19-24, 2022 BRYANT UNIVERSITY, SMITHFIELD, RI CHAIRS: Michael Fessler and Hongbo Chi VICE CHAIRS: Jeff Rathmell and Catherine Hedrick

• Repurposing of Bioenergetics in Innate Immunity Julie Magarian Blander, Luke O'Neill, Edward Pearce, Maxim Artyomov

• Metabolic Programming of Lymphocyte Function Peer Karmaus, Mark Boothby, Vijay Kuchroo, Erika Pearce, Claudia Kemper

• Metabolic-Epigenetic Crosstalk in Immunity Nancie Maciver, Mihai Netea, Jason Locasale, Russell Jones

• Sterols in Immunity Peter Ghazal, Steven Bensinger, Alan Tall, Chenqi Xu, Ping-Chih Ho

• Metabolic Programming in Autoimmune and Inflammatory

Diseases Erika Pearce, Laurence Morel, Navdeep Chandel, Cornelia

MAY 29-JUN 3, 2022 SALVE REGINA UNIVERSITY, NEWPORT, RI CHAIR: Amy Prieto VICE CHAIR: Jacqueline Veauthier

JUL 16-17, 2022 CHAIRS: Manushka Vaidya and Melissa Haskell

In Vivo Ultrasound Imaging

Yvonne Chen, Krishnendu Roy

Inorganic Chemistry Using the Versatility of Inorganic Elements to Address Grand Challenges in Health, Energy and the Environment

In Vivo Magnetic Resonance

• Cellular Immunoengineering Elizabeth Wayne, Wilson Wong,

Weyand

Ming Xu, Sangwon Suh, Yong Sik Ok, Paul Mativenga, Amy Landis

Rachael Seidler, Gordon Sarty

• Molecularly Engineered Immunotherapies Bruno Correia,

Immunometabolism in Health and Disease

and Processes Bhavik Bakshi, Gregory Keoleian, Yuan Yao, Vered Blass

• Circular Economy and Water Sustainability

• Novel Biomedical Targets for the Application of Magnetic

• Keynote Session: Modulating Immunity for Human

Yuanchao Hu, Bruno Basso, Ramzy Kahhat, Callie Babbitt, Joe Bozeman

• Implementing the Circular Economy in Industrial Systems • Advances of Circular Economy and Plastics Pollution

• Microimaging: Pushing the Limits with High Field Stephen

JUL 10-15, 2022 VENTURA BEACH MARRIOTT, VENTURA, CA CHAIRS: Rebecca Pompano and Bali Pulendran VICE CHAIRS: Susan Thomas and Madhav Dhodapkar

• Circular Economy Concepts for Zero-Carbon

Communities Shoshanna Saxe, Heinz Schandl, Kangkang Tong

Juchem

CHAIRS: Asheley Chapman and Veronica Davé

Pauliuk, Weslynne Ashton

• Advances in Methods: Circular Flows, Socioeconomic

Metabolism and Impact Modeling Alissa Kendall, Bing Zhu,

Joseph Ackerman, Charles Springer

Fusing Fields: Cross-Discipline Approaches to Probe and Modulate the Immune System

Circular Economy Transitions Valerie Thomas, Stefanie Hellweg • Scaling Up a Sustainable Circular Economy: Opportunities

• Keynote Session: Magnetic Resonance: Opportunities for

Immunochemistry and Immunobiology

Industrial Ecology Advancing the Circular Economy for Human and Planetary Wellbeing

• The GRC Power Hour™ Ana Mora, Claudia Kemper

• Immunity at Mucosal Sites Federica Sallusto, Janelle Ayres, • Sensors, Microbes and Inflammation Antonio Lanzavecchia,

• The GRC Power Hour™

Blander, Peter Ghazal, Janelle Ayres

• Cell Fate in Immunity and Metabolic Disease Lisa Bouchier-Hayes, Douglas Green, Gerald Shadel, Ira Tabas, Gokhan Hotamisligil

• Immunoregulation Laura Mackay, Gioacchino Natoli, Burkhard

• Neuromodulation Using Ultrasound Elisa Konofagou, Merritt

NEW!

• Harnessing Reactivity Andrew Borovik, Fabian Dielmann, George Stanley

Advances in New Ultrasonic Imaging Modes and Imaging Techniques Undergoing Clinical Evaluation

• The Heavy Elements Justin Walensky, Susanne Barth, Stosh

AUG 14-19, 2022 VENTURA BEACH MARRIOTT, VENTURA, CA CHAIRS: Michael Oelze and Kenneth Hoyt VICE CHAIRS: Michael Kolios and Oliver Kripfgans

• Interfacing Metals and Biology Elisa Tomat, Marcetta

• Beamforming and Speckle Reduction Jeremy Dahl, Alfred Yu,

• Spanning Molecules to Solids Natalia Shustova, Bart Bartlett,

Brett Byram, Muyinatu Bell

• Super-Resolution Ultrasound Imaging Mickael Tanter, Olivier Couture, Kirsten Christensen-Jeffries, Pengfei Song

• Development of Novel Contrast Agents Christy Holland, Mark Borden, Agata Exner, Klazina Kooiman

• Tissue Biomarkers and Tissue Characterization Kevin Parker, Gregory Czarnota, Jonathan Mamou, Kibo Nam

• Ultrasound Elasticity Imaging Kathy Nightingale, Marvin Doyley, Caterina Gallippi, Guy Cloutier

• Photoacoustic Imaging Roger Zemp, Sarah Burris, Carolyn Bayer,

Kozimor, Marinella Mazzanti, Eric Schelter Darensbourg, Emily Que

• Modes of Bonding Tracy Lohr, Francois Gabbai, Laurel Schafer, Mitch Smith, Theodore Betley Raffaella Buonsanti

• Condensed Matter and Its Applications Evgeny Dikarev, Jakoah Brgoch, Susan Kauzlarich, Lisa McElwee-White

• Physical Inorganic Chemistry Nancy Haegel, Kyle Lancaster, Joshua Vura-Weis, Ping Yang

• Energy Production and Storage Bart Bartlett, James Mayer, Hailiang Wang

• Inorganic Chemistry as a Driver of Innovation Jacqueline Veauthier, Polly Arnold, T. Don Tilley

• The GRC Power Hour™ Jacqueline Veauthier

Sarah Bohndiek

• Ultrasound Tomography Roberto Lavarello, James Wiskin, Neb Duric, Nicole Ruiter

• Ultrasound Therapy Flordeliza Villanueva, John Eisenbrey, Hong Chen, Kevin Hayworth

Inorganic Chemistry Applications of Inorganic Molecules and Materials in Magnetism, Catalysis and Energy Storage MAY 28-29, 2022 CHAIRS: Avery Baumann and Trevor Latendresse

Intermediate Filaments

Intrinsically Disordered Proteins

Linking the Cytoskeleton and Nucleus in Mechanobiology, Ageing, and Disease

How Life Harnesses Disorder: Emergent Functions of IDPs in Cells, Materials and Medicine

JUN 5-10, 2022 MOUNT SNOW, WEST DOVER, VT CHAIRS: Jan Lammerding and Roy Quinlan VICE CHAIRS: Elly Hol and Howard Worman

JUN 25-26, 2022

• Visualizing Filament Organization and Dynamics at the

Nanoscale Harald Herrmann, Birgit Lane, Ohad Medalia, Jennifer Lippincott-Schwartz

• Functional Insights into the Structure and Biophysics of

Intermediate Filaments Natasha Snider, Elaine Fuchs, Christopher Bunick, Sarah Koester, Steve McKnight

• Signaling and Cytoskeletal Crosstalk by Intermediate

Filaments Sandrine Etienne-Manneville, Gaudenz Danuser, Ming Guo, Pierre Thibault, John Eriksson • Connecting the Nucleus, Cytoskeleton and Extracellular

Environment Gregg Gundersen, Catherine Shanahan, Daniel Starr, Kathleen Green

• Integration of Muscle Mechanobiology by Intermediate

Filaments in Health and Disease Dennis Discher, Benjamin Prosser, Shenhav Cohen, Brian Glancy

• Linking Intermediate Filaments to Neurodegenerative

Diseases Ronald Liem, Pascale Bomont, Sanjay Kumar, Jean-Pierre Julien, Milos Pekny

• Progenitors, Senescence and Cancer Dennis Roop, Ganna Bilousova, Andy Xiang, Pierre Coulombe

• Mechanistic Insights into Intermediate Filament Diseases Cecilia Sahlgren, Nicole Schwarz, Dolores Perez-Sala, Kurt Zatloukal, Karen Ridge

• Emerging Therapeutic Approaches for Intermediate

Filament-Based Diseases Gisele Bonne, Lori Wallrath, Stephen Young, Colin Stewart

• The GRC Power Hour™

Intermediate Filaments Bridging the Gap Between Molecules and Tissue: How Intermediate Filaments Affect our Health JUN 4-5, 2022 CHAIR: Rebecca de Leeuw

CHAIRS: Alexander Chin and Erik Martin

Ion Channels Molecular Mechanisms of Electrical Signaling in Health and Disease JUL 10-15, 2022 MOUNT HOLYOKE COLLEGE, SOUTH HADLEY, MA CHAIR: Brad Rothberg VICE CHAIRS: Teresa Giraldez and Baron Chanda

• Keynote Session: Ion Channels in Excitable Cells Teresa Giraldez, Sudha Chakrapani, Roderick MacKinnon

• Anion Channels in Health and Disease Alessio Accardi, Anne

The Functional Role of Disorder in Biological Systems JUN 26-JUL 1, 2022 LES DIABLERETS CONFERENCE CENTER, LES DIABLERETS, SWITZERLAND CHAIRS: Elizabeth Rhoades and Philipp Selenko VICE CHAIRS: Birthe Kragelund and Tanja Mittag

• Keynote Session: Mechanisms of IDPs in Signalling Birthe Kragelund, Vincent Hilser, Martha Cyert

• Functional Mechanisms of IDPs Lucia Chemes, Carrie Partch, Jennifer Hurley, Antonina Roll-Mecak

• Tools and Methods for IDPs Edward Lemke, Kresten Lindorff-Larsen, Cesar Cuevas-Velazquez, Andrea Soranno, Samrat Mukhopadhyay

• IDPs in Disease Perdita Barran, Carlos Castaneda, Lucia Chemes, Hoi Sung Chung, Toby Gibson

• Evolution and Proteomics Toby Gibson, Allan Drummond, Agnes Toth-Petroczy, Paula Picotti

• Biomolecular Condensates and Biomaterials Samrat Mukhopadhyay, Ali Miserez, Shana Elbaum-Garfinkle, Lucas Pelkmans, Felipe Quiroz, Joan-Emma Shea

• Dynamic Ensembles Peter Wright, Shahar Sukenik, Katherine Aurelia Ball, Hagen Hofmann

• IDPs in the Nucleus Keith Dunker, Ibrahim Cisse, Lucia Strader, Sara Cuylen-Haering, Shasha Chong, Liesbeth Veenhoff

• Keynote Session: Dynamic Ensembles Tanja Mittag, Martin Blackledge, Jane Dyson

• The GRC Power Hour™ Martha Cyert, Lucia Strader

communities that support career advancement for junior and senior scientists alike. GRCs in recent years have helped promote diversity and inclusion among their participants.

”

DR. CYNTHIA BURROWS, University of Utah

Carlson, Merritt Maduke, Zhaozhu Qiu, Jue Chen

• Mechanisms of Voltage-Sensing and Gating Baron Chanda, Jian Payandeh, Kenton Swartz, Eduardo Perozo, Crina Nimigean

• Dynamic Approaches to Bridge Structure and Function William Kobertz, Chris Ahern, Stephanie Heusser, Simon Scheuring

• Cardiac Ion Channels and their Modulation David Jones, Peter Larsson, Cathy Proenza, Jianmin Cui, Gail Robertson

• Calcium Channel Complexes and Cell Signaling Ivy Dick,

Ionic Liquids Linking Ionic Liquid Structure, Reactions and Applications Across Temperatures AUG 6-7, 2022 CHAIRS: Emmanuel Varona-Torres and Hemant Choudhary

Jean-Ju Chung, Henry Colecraft, Amy Lee, Claudia Moreno

• Channel Pharmacology and Channelopathies Valeria Vasquez, Paul Slesinger, Stephen Tucker, Andrea Bruggemann, Andrea Meredith

• Glutamate Receptors from Structure to Synapse Vasanthi Jayaraman, Hiro Furukawa, Ingo Greger, Gabriela Popescu, Lonnie Wollmuth, Andrew Plested

• TRP and Other Sensory Channels Vera Moiseenkova-Bell, Sebastian Brauchi, Vanessa Ruta, Elena Gracheva, Lejla Zubcevic, Martin Chalfie, Julio Cordero-Morales

• The GRC Power Hour™

Ion Channels Molecular Mechanisms of Electrical Signaling in Health and Disease JUL 9-10, 2022

Intrinsically Disordered Proteins

GRCs are an excellent “mechanism for building

CHAIRS: Alexandria Miller and Valeria Kalienkova

Lignin Realizing Lignin's Potential in Biorefining by Bridging Plant Biology, Chemistry and Engineering JUL 31-AUG 5, 2022 STONEHILL COLLEGE, EASTON, MA CHAIRS: Yuriy Román and Katalin Barta VICE CHAIRS: Laura Bartley and Jeremy Luterbacher

• Keynote Session: Converging Disciplines for the Sustainable

Valorization of Lignin Jeremy Luterbacher, Lacey Samuels, Bert Weckhuysen

• Methods to Tailor Lignin Biosynthesis In Planta Claire Halpin, Taku Demura, Aymerick Eudes, Shinya Kajita, Ohkamae Park

• Designing Enzymatic Systems for Lignin Depolymerization Taina Lundell, Davinia Salvachua, Steven Singer, Takashi Watanabe

• Catalytic Lignin Depolymerization and Upgrading Seema Singh, Emiel Hensen, Roberto Rinaldi, Chen Zhao

Ionic Liquids

• Convergent Microbial Lignin Conversion Strategies Timothy

Linking Ionic Liquid Structure, Reactions and Applications Across Temperature

• Lignin from an Industrial Perspective Jean-Pierre Lindner,

AUG 7-12, 2022 GRAND SUMMIT HOTEL AT SUNDAY RIVER, NEWRY, ME CHAIR: Paul Trulove VICE CHAIR: Jared Anderson

• Keynote Session: The Future of Ionic Liquids Robert Mantz, Tom Welton, Mark Shiflett

• Natural and Synthetic Polymers Luke Haverhals, David Durkin, Stephen Paddison

• Linking Biology and Ionic Liquids Paula Berton, Patrick Dennis, Eden Tanner

• Electrochemical Applications of Ionic Liquids Hunaid

Donohue, Tim Bugg, Lindsay Eltis, Guillermina Hernandez Raquet Raymond Buser, Michael Rushton, Karolien Vanbroekhoven, Christian Dahlstrand, Ian Klein, Sander Van den Bosch

• Tools and Methods for the Analysis, Visualization and

Structural Elucidation of Lignin Yuki Tobimatsu, Simon Hawkins, Susannah Scott, Tuo Wang

• Tailoring Chemical Routes for the Synthesis of Direct and

Functional Replacement Products from Lignin Pieter Bruijnincx, Martin Lawoko, Mojgan Nejad, Chris Saffron, Ning Yan

• Incorporating Process Engineering in the Lignin Upgrading

Workflow Sankar Nair, Christos Maravelias, Junyong Zhu • The GRC Power Hour™ Claudia Crestini, Rebecca Smith

Nulwala, Jesse McDaniel, Cristina Pozo-Gonzalo

• Ionic Liquids Beyond the Boundaries Sheng Dai, James Davis, Claudio Margulis, Isiah Warner

• The Interface Between Ionic Liquids and Deep Eutectic

Solvents Burcu Gurkan, Isabel Marrucho, Karen Edler, Malgorzata Swadzba-Kwasny

• Structure-Property Relationships in Ionic Liquids Hugh De Long, Ralf Ludwig, Edward Maginn, Joan Brennecke

• Ionic Liquids in Future Sustainable Technologies Jason Hallett, Jason Bara, Agnieszka Brandt-Talbot, Nolene Byrne, Elizabeth Biddinger

• Late-Breaking Topics Jared Anderson • The GRC Power Hour™ Burcu Gurkan, Jared Anderson

Lipidomics

NEW!

Lipidomics and Decoding Life: From the Technology and Biology Landscapes to Clinical Adaptation AUG 7-12, 2022 JORDAN HOTEL AT SUNDAY RIVER, NEWRY, ME CHAIRS: John Bowden and Kim Ekroos VICE CHAIRS: Gerhard Liebisch and Xianlin Han

• Lipidomics in Decoding Biology William Griffith, Scott Summers, Vytas Bankaitis

• Lipidomics in Human Health and Disease Edward Dennis, Michal Holcapek, Michael Kiebish, Gilbert Di Paolo

• Harmonization and Standardization in Lipidomics Valerie O'Donnell, Martin Giera, Markus Wenk, Jeffrey McDonald

• Novel Lipidomic Mass Spectrometry Strategies Christer Ejsing, Shane Ellis, Christoph Thiele, André Nadler

• Clinical and Translational Lipidomics Veronica Anania, Daisuke Saigusa, Livia Eberlin

• Lipidomics Data Dimensions and Biological Interpretation John McLean, Erin Baker, Steffany Bennett, Andrej Shevchenko, Yu Xia

• Resolving Lipid Metabolic Networks Gavin Reid, Nathan Hatcher, Jace Jones, Charles Serhan

Liquid Biopsy for Cancer

Mammalian Reproduction

Emerging Liquid Biopsy Technologies for Early Detection, Disease Profiling and Monitoring of Cancer

Safeguarding Fertility for the Present and Future

JUN 18-19, 2022

• Integration of Lipidomics with Genomics, Proteomics and

Metabolomics Harald Koefeler, Bjoern Titz, Peter Meikle • The GRC Power Hour™ Erin Baker

Lipoprotein Metabolism New Lipid and Lipoprotein Genes, Pathways and Therapies JUN 5-10, 2022 SOUTHBRIDGE HOTEL & CONFERENCE CENTER, SOUTHBRIDGE, MA CHAIRS: M. Mahmood Hussain and Kiran Musunuru VICE CHAIRS: Marlys Koschinsky and Daisy Sahoo

• Keynote Session: Genetics of Lipids and Cardiovascular

Disease Marlys Koschinsky, Sekar Kathiresan • The Lipoprotein Lipase Pathway Ira Goldberg, Anne Beigneux, Karin Bornfeldt, Sander Kersten, Xiao Wang

• Therapeutic Approaches to Modulate Plasma Lipids and

Lysosomes and Endocytosis Physiological Adaptations of the Endo-Lysosomal System JUN 19-24, 2022 PROCTOR ACADEMY, ANDOVER, NH CHAIR: Christopher Burd VICE CHAIR: Phyllis Hanson

• Lysosomes and the Control of Cellular Metabolism Suzanne Pfeffer, Robert Piper, Andrea Ballabio, Erik Jorgensen, Jennifer Stow

• The Endo-Lysosomal System and Disease Scott Emr, Leon Murphy, Rushika Perera, Marco Sardiello, Harald Stenmark, Joseph Mindell

• Entering Cells Lauren Jackson, Frances Brodsky, Gunther Hollopeter, Min Wu

• Inter-Organelle and Inter-Cellular Communication Philip Stahl, Sandra Cristina Paiva, Guillaume van Niel, Meng Wang, Lois Weisman, Roberto Zoncu

• Roles of the Endosomal Network in Organismal

Lipoproteins Mary Sorci-Thomas, Marina Cuchel, Bruce Given,

Physiology Tomas Kirchhausen, Margaret Robinson, Max Gutierrez,

Viktoria Gusarova, Richard Lee

Francesca Peri, Avital Rodal

• Noncoding RNAs in Lipoprotein Metabolism Katey Rayner, Kathryn Moore, Muredach Reilly, Tamer Sallam, Yajaira Suarez

• Lipid Metabolism in Adipose Tissue Loredana Quadro, Robert Farese, Susan Fried, Sujith Rajan, Judith Storch

• The Post-Genomic Era in Lipoprotein Metabolism Masahiro Koseki, Robert Bauer, Mary Haas, Elizabeth Tarling, Noam Zelcer

• Permanent Modification of Lipid Levels Daisy Sahoo, Alexandra Chadwick, Steven Farber, Lily Hoffman-Andrews, Klaus Ley

• Lipoproteins Gissette Reyes-Soffer, Ashira Blazer, Edward Fisher,

• The Lysosome, Autophagy and Cellular Catabolism Markus Babst, James Hurley, Florian Froehlich, Thomas Melia, Anne Simonsen, Michael Overholtzer

• Late-Breaking Topics Alexander Sorkin, Michael Bassik, Yamuna Krishnan

• Sorting and Trafficking in the Endosomal Network Elizabeth Conibear, Juan Bonifacino, Michael Marks, Andreas Mayer, Peter Cullen

• Lysosome-Like Organelles Fred Maxfield, Graca Raposo

Research Qing Miao, Chiara Giannarelli, Alan Remaley • The GRC Power Hour™ Marlys Koschinsky, Daisy Sahoo

Lipoprotein Metabolism Molecular Mechanisms of Lipid Metabolism in Health and Disease JUN 4-5, 2022 CHAIR: Paul Li-Hao Huang

Liquid Biopsy for Cancer JUN 19-24, 2022 MOUNT HOLYOKE COLLEGE, SOUTH HADLEY, MA CHAIRS: Klaus Pantel and Shana Kelley VICE CHAIRS: Min Yu and Rosandra Kaplan

• Grand Challenges in Liquid Biopsy Research Min Yu, Howard Scher

• The Biology Behind Liquid Biopsy Biomarkers Rosandra Kaplan, John Condeelis, Jacky Goetz, Jean Paul Thiery

• Genotypic CTC and ctDNA Analysis Daniel De Carvalho, Wai Kei Jacky Lam, Jacqui Shaw, Brian Dougherty

• Phenotypic and Functional Analysis for Liquid Biopsy Wai Kei Jacky Lam, Nicola Aceto, Matt Trau, Catherine Alix-Panabieres, Ryan Sullivan

• High Performance Analytical Technologies for Liquid Biopsy Shannon Stott, Amy Herr, Daniel Chiu, Vanessa Jonsson

• Liquid Biopsy and Clinical Utility Harriet Wikman, Andrew Armstrong, Alison Allan, Ellen Heitzer, Ralph Graeser

• Early-Career Investigator Presentations Amy Herr • Extracellular Vesicles Catherine Alix-Panabieres, David Lyden, Yong Zeng, Shannon Stott

• New Liquid Biopsy Biomarkers Alison Allan, Michael Sixt, Daniel Chiu, Harriet Wikman

• The GRC Power Hour™

Mammary Gland Biology Normal Breast Biology and Its Relationship to Breast Cancer Initiation and Progression MAY 29-JUN 3, 2022 RENAISSANCE TUSCANY IL CIOCCO, LUCCA (BARGA), ITALY CHAIRS: Maria Vivanco and Beatrice Howard VICE CHAIRS: Russell Hovey and Senthil Muthuswamy

• Keynote Session: Breast Stem Cell Biology Barry Gusterson, Connie Eaves

• Normal Breast Biology: Progenitor and Stem Cells Renee Van Amerongen, Marja Mikkola, Pamela Cowin, Lone Ronnov-Jessen

• Abnormal Breast Biology: Precancerous Lesions

(DCIS) Fariba Behbod, Louise Jones, Jelle Wesseling • Heterogeneity in Breast Cancer Walid Khaled, Rama Khokha, Joan Brugge, Helen Piwnica-Worms

• Molecular Alterations During Pregnancy and

Lactation Russell Hovey, Carles Lerin, Natalie Shenker • Residual Disease and Metastasis Eva Gonzalez-Suarez, Marianna Rapsomaniki, Douglas Hanahan, Fatima Mechta-Grigoriou

• Hormone Receptor Signaling Senthil Muthuswamy, Cathrin Brisken, Leonie Young

• Novel Approaches to Study Mammary Development and

Disease Gillian Farnie, Michael Lewis, Joaquin Arribas, Spiros Linardopoulos

• Keynote Session: Breast Stem Cell Biology and

Translational Breast Cancer Research John Stingl, Geoffrey Lindeman

• The GRC Power Hour™ Leonie Young

• The GRC Power Hour™ Sandra Cristina Paiva, Phyllis Hanson

Roop Mallik, Nathalie Pamir, Lloyd Ruddock, Shadab Siddiqi

• Cutting-Edge Technologies for Lipid and Lipoprotein

CHAIRS: Margeaux Marbrey and Klementina Fon Tacer

CHAIRS: Fredrik Thege and Nykia Walker

• Role of the Environment on the Lipidome Nancy Denslow, Laila Abdullah, Jeremy Koelmel, Kuniyuki Kano

AUG 13-14, 2022

Mammary Gland Biology Lysosomes and Endocytosis Physiology, Functions and Interactions of the Endo-Lysosomal System in Health and Disease JUN 18-19, 2022

Molecular and Cellular Processes Driving Mammary Gland Development and Breast Cancer MAY 28-29, 2022 CHAIRS: Qiang Lan and Giusy Tornillo

CHAIR: Roni Levin Konigsberg

Mammalian Reproduction From Regulatory Mechanisms to Practical Applications

Marine Microbes The Interconnected Microbial Ocean

AUG 14-19, 2022 MOUNT SNOW, WEST DOVER, VT CHAIRS: Margaret Petroff and Kyle Orwig VICE CHAIRS: Richard Freiman and Joan Jorgensen

MAY 29-JUN 3, 2022 LES DIABLERETS CONFERENCE CENTER, LES DIABLERETS, SWITZERLAND CHAIR: Corina Brussaard VICE CHAIR: Lasse Riemann

• Building Blocks for Reproduction: Eggs, Sperm and Uterus

• Pathogenic Microbe Interactions and Their Influence on

Julie Kim, Francesca Duncan, Stefan Schlatt, Thomas Spencer

• Stem Cells in Reproductive Processes Robin Hobbs, Katsuhiko Hayashi, Margherita Turco, Ina Dobrinski

• Developmental Biology and Sex Determination Lane Christenson, Helen Jones, Diana Laird, Fei Zhao

• Internal and External Influences on Reproduction Miguel Brieño-Enriquez, Sean Limesand, Sherman Silber, James Turner, Ans Van Pelt

• Bioengineering for Improving Reproductive Outcomes Monica Laronda, Jon Oatley, Anthony Perry, Ariella Shikanov

• Immune Function in Reproductive Biology Tony De Falco, Maria Battistone, Jannette Dufour, Tippi MacKenzie, Dorothy Sojka

• Reproduction in the Age of Omics John Schimenti, Pat Lonergan, Roser Vento-Tormo, Miles Wilkinson

• Molecular and Genetic Control of Reproduction Sue Hammoud, Nehemia Alvarez, Sarah England, Chen Chen

• Keynote Session: Determinants of Reproductive Outcomes

and Disease Richard Freiman, Joan Jorgensen, Asgerally Fazleabas, Mary Ann Handel

• The GRC Power Hour™

Biogeochemical Cycling Curtis Suttle, Steven Wilhelm, Rui Zhang • Single Celled Microbes Versus Assembled Microbial

Communities Martin Ackermann, Roman Stocker, Knut Drescher, Nicole Dubilier

• Evolution of Marine Microbes Alexandra Worden, Rogier Braakman, Anja Spang, Kasper Kjeldsen, Gabrielle Rocap

• Microbial Predator-Prey Interchange in Relation to Marine

Ecological Theories Thomas Kiorboe, Susanne Wilken, Selina Vage, Ramon Massana

• Synergistic Microbe-Microbe and Microbe-Host Connections

and Communication Justin Seymour Seymour, Hanna Farnelid, Jonathan Zehr, Torsten Thomas, Michael Sweet

• The Complex Marine Microbiomes Captured in Networks

and Ecosystem Models Naomi Levine, Christian Mueller, Victoria Coles, Marina Levy

• Environmental Shaping of Microbial Communities and

Vice Versa Xose Anxelu Moran, Laura Alonso-Saez, Daniele Bianchi, Ed Hall, Clara Ruiz-González

• Living at the Ocean’s Boundaries Anne Dekas, Filip Meysman, Heide Schulz-Vogt, Sarah Hu

• A Changing Ocean: Challenges to Overcome for Microbial

Functional Success Oded Beja, Charmaine Yung, Stephen Giovannoni, Osvaldo Ulloa, Katherine Mackey

• The GRC Power Hour™ Charmaine Yung, Gabrielle Rocap

Marine Microbes Integrative Microbial Oceanography

Mechanisms of Epilepsy and Neuronal Synchronization

MAY 28-29, 2022

Approaching Complexity in Neuroscience and Epilepsy

Molecular Mechanisms and Regulation of Sexual Reproduction

JUL 30-31, 2022

JUN 4-5, 2022

CHAIRS: Melanie McNally and Wesley Clawson

CHAIRS: María Angélica Bravo Núñez and Katherine Billmyre

CHAIRS: B. B. Cael and Chase James

Meiosis

Mechanical Systems in the Quantum Regime

Medicinal Chemistry

Membrane Transport Proteins

Quantum Phononics for Fundamental Measurements and Quantum Technology

Innovations in Drug Discovery and Enabling Technologies

Biomedical Transporters: Physiology, Dysfunction and Targets of Pharmacotherapy

JUN 19-24, 2022 VENTURA BEACH MARRIOTT, VENTURA, CA CHAIRS: Cindy Regal and Klemens Hammerer VICE CHAIRS: Thomas Purdy and Amir Safavi-Naeini

AUG 7-12, 2022 COLBY-SAWYER COLLEGE, NEW LONDON, NH CHAIR: Cynthia Parrish VICE CHAIR: Michael Ellis

JUN 12-17, 2022 REY DON JAIME GRAND HOTEL, CASTELLDEFELS, SPAIN CHAIR: Aurelio Galli VICE CHAIRS: Renae Ryan and Susan Ingram

• Acoustic Waves and Brillouin Optomechanics Amir

• Small Molecule Approaches for Immuno-Oncology Laura

• Channelopathies and Transportopathies Renae Ryan, Al George,

Safavi-Naeini, Peter Rakich, Konrad Lehnert

• Gravitational Wave Detectors Thomas Purdy, Nergis Mavalvala, Martin Hewitson, Yanbei Chen, David McClelland

• Nonreciprocity and Chirality in Optomechanics Ewold Verhagen, Anja Metelmann, Haitan Xu, Aashish Clerk

• Levitated Optomechanics and Electromechanics Tongcang Li, Benjamin Stickler, Markus Aspelmeyer, Hendrik Ulbricht, Jack Harris

• Fundamental Tests with Mechanical Sensors Yiwen Chu, Swati Singh, Holger Mueller, Jacob Taylor

• Heralding Single Phonons and Quantum Measurements Aashish Clerk, Simon Groeblacher, Magdalena Zych, Christophe Galland, Eugene Polzik

• Quantum Electromechanical Devices Eva Weig, Adrian Bachtold, John Teufel, Silvia Viola Kusminskiy

• Spin Coupling to Nanomechanics Donghun Lee, Christian Degen, Ania Bleszynski-Jayich, Raffi Budakian, Philipp Treutlein

• Late-Breaking Topics John Teufel • The GRC Power Hour

™

Jack Harris, Eva Weig

Mechanical Systems in the Quantum Regime Optomechanical Systems Enabling Novel Quantum-Enhanced Technologies and Tests of Fundamental Physics JUN 18-19, 2022 CHAIRS: Charles Brown and Martin Koppenhoefer

Mechanisms of Epilepsy and Neuronal Synchronization Molecular and Network Complexity in the Epileptic Brain JUL 31-AUG 5, 2022 REY DON JAIME GRAND HOTEL, CASTELLDEFELS, SPAIN CHAIRS: Jeffrey Noebels and Chris Dulla VICE CHAIRS: Helen Scharfman and Viji Santhakumar

• Complexity in Epilepsy Gemma Carvill, Danielle Bassett, Liset Menendez de la Prida

• Local and Long-Range Circuitry Esther Krook-Magnuson, Yoav Adam, Peyman Golshani

• Cell Type-Specific Contributions to Seizures Ivan Soltesz, Mauro Costa-Mattioli, Gordon Fishell

• Synaptic and Network Homeostasis Istvan Mody, Seth Grant, Eve Marder, Joseph Raimondo

• Glial Signaling and Epileptogenesis Amy Brewster, Ukpong Eyo, Phil Haydon

• Developing Circuits Heinz Beck, Arnold Kriegstein, Annapurna Poduri, Beatriz Rico, Elsa Rossignol

• New Gene Targets and Therapies Dimitri Kullmann, Amy Brooks-Kayal, Stefanie Dedeurwaerdere, Harald Sontheimer

• Oscillations, Rhythms and Network Dynamics Jennifer Gelinas, Christophe Bernard, Laura Ewell, Vikaas Sohal, Rafael Yuste

• Epigenetic and Metabolic Targets in Epileptic Brain Jeannie Chin, David Henshall, Katja Kobow

• The GRC Power Hour™

D'Agostino, Julia Haas, Eric Miller, Louis Chupak, Nigel Swain

• Emerging Technologies: From In Silico to Implementation H. Rachel Lagiakos, Steve Swann, Jason Burch, Falgun Shah, Heike Schoenherr

• Therapies Targeting Diseases of the CNS Emily Peterson, Peter Fuller, Duane Burnett, Kevin Guckian

• Synthetic Technologies to Enable Medicinal Chemistry Amy Hart, Jesus Alcazar, Rachel Grainger, Vincent Colandrea, Alison Wendlandt

• Recent Advances in Modulators of Protein-Protein

Interactions Alex Cortez, Eric Fischer, Jim Henderson • Strategies for Overcoming Drug Safety Liabilities Izzat Raheem, Iyassa Sebhat, Michael Rudd, Grace Chuang, Patrizio Mattei

• New Directions in Beyond 500 Compounds: From PK to the

Clinic Christopher Nasveschuk, Andrew Scholte, John Link, Matthew Weiss

• Late-Breaking Topics: First Disclosures of Clinical

Candidates Meredeth McGowan, Michael Graupe, Michelle Garnsey, Scott Edmondson

• Keynote Session Michael Ellis, Rosana Kapeller • The GRC Power Hour™

Hanne Poulsen, Jeffrey Rothstein

• Targeting Transporters for Pharmacotherapies Sandra Hewett, Erin Calipari, Nancy Carrasco, Amy Newman, Manuel Palacin, Robert Vandenberg

• Transporter Function and Dysfunction in Metabolism,

Diabetes and Obesity Habibeh Khoshbouei, Zachary Freyberg, Sophie Hambleton, Amira Klip, Michael Koettgen

• Invertebrates as Animal Models to Study Transporter

Functions Randy Blakely, Freja Herborg, Susan Amara, Laura Bianchi, Lucia Carvelli, David Krantz

• Na, K-ATPase and Related Pumps Imogen Coe, Matthias Hediger, Jonathan Javitch, Poul Nissen, Daniela Pietrobon

• Neurological and Neuropsychiatric Disorders: Transporters

at Play Rajini Rao, Heinrich Matthies, Haley Melikian, Gaia Novarino, Harald Sitte

• New Strategies, Ideas and Techniques to Study Membrane

Protein Structure-Function and Trafficking Ulrik Gether, Olga Boudker, Sergio Grinstein, Parastoo Hashemi, Eduardo Perozo

• Peptides, Hormones, and Neurotransmitter Release: The

Importance of Transporters in the Gut and Brain Michael Freissmuth, Susan Ingram, Eric Gouaux, Robert Edwards, Naoki Yamanaka

Medicinal Chemistry

• Detailing Mechanisms of Importers and Exporters Roxanne

Principles, Strategies and Case Studies in Medicinal Chemistry and Drug Discovery

• The GRC Power Hour™ Imogen Coe

Vaughan, Isabelle Baconguis, Hassane Mchaourab, Christine Ziegler

AUG 6-7, 2022 CHAIR: Erin DiMauro

Meiosis Diverse and Conserved Molecular Mechanisms Preventing Aneuploidy During Gamete Production JUN 5-10, 2022 COLBY-SAWYER COLLEGE, NEW LONDON, NH CHAIR: Paula Cohen VICE CHAIR: Jeff Sekelsky

• Physical Properties and Organization of the Synaptonemal

Complex Ricardo Benavente, Scott Hawley, Nancy Kleckner, Ofer Rog • Placement and Induction of Double Strand Breaks (DSB) Bernard de Massy, Corentin Claeys Bouuaert, Monica Colaiacovo

• DSB Processing and Pathway Choice Douglas Bishop, Diana Libuda, Michael Lichten, Mathilde Grelon

• Chromosome Dynamics, Cohesion and Pairing Akira Shinohara, Nicole Crown, Denise Zickler

• Chromatin Organization, Gene Expression and Epigenetic

Control of Meiosis Kevin Corbett, Florencia Pratto • Crossover Designation, Maturation and Homeostasis Neil Hunter, Petr Cejka, Francesca Cole, Ian Henderson

• Meiotic Drive Mechanisms and Evolution Sarah Zanders, Kirsten Bomblies, Abby Dernburg, Amanda Larracuente, Michael Lampson

• Spindle Assembly, Chromosome Segregation and Checkpoint

Control Needhi Bhalla, Binyam Mogessie • Post-Translational Modifications in Meiosis Anne Villeneuve, Peter Carlton, Hiro Ohkura, Yumi Kim

Membrane Transport Proteins The Structure-Function Relationship of Transporters in Health and Disease JUN 11-12, 2022 CHAIRS: Susanna Concilio and Eric Figueroa

Membranes: Materials and Processes Growing Convergence in Membrane Separations Research JUL 31-AUG 5, 2022 COLBY-SAWYER COLLEGE, NEW LONDON, NH CHAIRS: Isabel Escobar and William Phillip VICE CHAIRS: J.R. Johnson and Lucy Camacho

• Keynote Session: Interfacial Engineering of Membranes for

Environmental Applications Audie Thompson, Steven Weinman, Dibakar Bhattacharyya, Lidietta Giorno • Rational Design of Membrane Materials Jamie Hestekin, Christopher Arges, Hee Oh, Qilin Li, Zachary Smith, Haiqing Lin

• Process Optimization and Intensification William Tarpeh, Ngai Yin Yip, Michelle Dose, Uwe Beuscher

• Membrane Manufacturing Ramy Swaidan, Tequila Harris, Marcus Worsley, Maria Coleman, Glenn Fredrickson

• Real-Time Process Control and Membrane Fouling Shudipto Dishari, Johannes Vrouwenvelder, Daniel Miller, Jessica Schiffman

• Composite Membrane Structures Cristiana Boi, Marta Hatzell, Sibudjing Kawi, Andrea Schaefer, Nicholas Kotov

• Reactive, Emerging and Hybrid Membrane Processes Kerri Hickenbottom, Lauren Greenlee, Suzana Nunes, Seth Darling

• Emerging Industrial Separations TorOve Leiknes, Alexander Lopez, Chunqing Liu, Stephen Ritchie, Christina Carbrello

• Keynote Session: From Lab-Scale Discoveries to Industrial

Separation Processes Ayse Asatekin, Robert Schucker, William Koros • The GRC Power Hour™ Jamie Hestekin, Christina Carbrello

Membranes: Materials and Processes Connecting Pathways Between Molecular Design and Module Commercialization in Membrane Science JUL 30-31, 2022 CHAIRS: Gabrielle Lawrence and Matthew Rivera

Microbial Stress Response

Microbiology of the Built Environment

Bacterial Mechanisms for Sensing, Responding and Adapting to Stress

Microbes at the Interface of Water, Air and Human Health in Built Environments

JUL 17-22, 2022 MOUNT HOLYOKE COLLEGE, SOUTH HADLEY, MA CHAIRS: Michael Laub and Jade Wang VICE CHAIRS: Amy Schmid and Peter Chien

JUN 19-24, 2022 WATERVILLE VALLEY, WATERVILLE VALLEY, NH CHAIR: Kyle Bibby VICE CHAIR: Amy Pruden

• Cell Envelope Stress Eduardo Groisman, Jean-Francois Collet, Petra

• Linking Building Microbiomes and Health Karen Dannemiller,

Levin, Natividad Ruiz, Allison Williams

• Replication Stress William Navarre, Susan Rosenberg, Lyle Simmons, Jan-Willem Veening

Metallocofactors

• Stress of Other Cells Petra Levin, Marie Elliot, Daniel Wall, Chris Waters

Bioinorganic Active Sites that Drive Challenging Chemical Conversions

• Temperature, Oxidative and Metal Stress Joan Slonczewski,

JUN 5-10, 2022 SALVE REGINA UNIVERSITY, NEWPORT, RI CHAIR: Serena DeBeer VICE CHAIR: Kyle Lancaster

• Energy and Metabolic Stress Peter Chien, Lars Dietrich, N. Cecilia

• Frontiers of Metallocofactor Design Kelly Chacon, Yi Lu, Andrew

• Stress of Phage and Mobile Genetic Elements Lyle Simmons,

Borovik

• Hydrogenase: From Models to Enzymes R. David Britt, Alison Parkin, Hannah Shafaat, Jason Shearer, Ulf-Peter Apfel

• Protein Engineering Lisa Olshansky, Akira Onoda, Ross Anderson, Julie Renner

Frederic Barras, Carol Gross, John Helmann, Arash Komeili Martinez-Gomez, Caroline Harwood

• Regulatory Systems for Stress Amy Gehring, Mark Buttner, Sean Crosson, Susan Gottesman, Gisela Storz Alan Grossman, Kim Seed, Cari Vanderpool

• Stress of Being in a Host Marie Elliot, Sophie Helaine, William Navarre • Proteotoxic and Translational Stress Amy Schmid, Gert Bange, Pierre Genevaux, Daniel Kearns

• The GRC Power Hour™

Chuck Gerba, Laura-Isobel McCall

• Drinking Water Microbiome Sarah Haig, Shantini Gamage, Frederik Hammes, Ameet Pinto

• Extreme and Confined Environments Amy Pruden, Charlie Ott, Trinity Hamilton

• Antibiotic Resistance Erica Hartmann, Kerry Hamilton, Tao Yan • Microbiology of Sewage Collection Systems Jordan Peccia, Lydia Bourouiba

• Microbiology of the Built Environment in the Developing

World Krista Wigginton, Joe Brown, Kara Nelson, Amy Pickering • Microbiologically-Informed Green Engineering Design Mark Hernandez, Timothy Julian, William Rhoads

• Standardizing Built Environment Microbiological Methods Timothy Julian, Andrew Jackson, Robert McLean, Caitlin Proctor

• Biofilms Robert McLean, Scott Kelley • The GRC Power Hour™ Amy Pruden

• Iron-Sulfur Biochemistry Patricia Dos Santos, Sean Elliott, Daniel Suess, Seigo Shima

• CO and CO2 Conversion by Enzymes and Models Inês Pereira, Holger Dobbek, Abhishek Dey, Christine Thomas

• Lanthanide Metallobiochemistry Rebecca Abergel, Cathleen Zeymer, N. Cecilia Martinez-Gomez, Joseph Cotruvo, Jr.

Microbial Stress Response Microbial Sensing, Signaling and Survival in Stress JUL 16-17, 2022 CHAIRS: Mona Orr and Jan-Ulrik Dahl

• Recent Advances in Nitrogenase Research Oliver Einsle, Shelley Minteer, Akif Tezcan, Simone Raugei

• Water Oxidation in Enzymes and Models Theodor Agapie, Yulia Pushkar, Nicholas Cox, Julio Lloret Fillol, Greta Patzke

• C-H Activation by Copper William Tolman, Amy Rosenzweig, Paul Walton

• The GRC Power Hour™

Metals in Medicine

Microbial Toxins and Pathogenicity Mechanisms of Action, Detection and Evasion of Microbial Toxins JUL 10-15, 2022 SOUTHBRIDGE HOTEL & CONFERENCE CENTER, SOUTHBRIDGE, MA CHAIR: Heran Darwin VICE CHAIR: Mary O'Riordan

Advancing the Use of Metal-Based Compounds and Nanotheranostics for Personalized Medicine

• Keynote Session: Virulence Regulation During

JUN 26-JUL 1, 2022 PROCTOR ACADEMY, ANDOVER, NH CHAIRS: Edith (Phoebe) Glazer and Angela Casini VICE CHAIRS: Carolyn Anderson and Anne-Kathrin Duhme-Klair

• Bacterial Toxins: Structure, Function and Outcome

• Keynote Session: Supramolecular Metal-Based Molecules

for Biomedical Applications Michael Hannon, Makoto Fujita, Shawn Chen, Wenbin Lin

• Clinical Advances for Metals in Medicine Walter Berger, Sherri McFarland, Thomas Meade, Linda Vahdat, Anton Simeonov

• Catalysis in Cells Luca Salassa, Loi Do, José Luis Mascareñas, Katsunori Tanaka

• Novel Metallomics Methods and Tools Ana Maria Costa Ferreira, Samuel Meier-Menches, Eric Gale, Alessandra Magistrato, Sarah Michel, Nigel Robinson, Sharon Ruthstein, Janet Morrow

• Late-Breaking Topics Carolyn Anderson, Anne-Kathrin Duhme-Klair, Camilla Abbehausen, Eszter Boros, Orazio Vittorio

• Novel Chelation Strategies and Applications for

Radionuclides and Contrast Agents Eric Gale, Rebecca Abergel, Peter Caravan, Jason Lewis, Darren Magda, Katherine Vallis

• Essential Metals in Disease Mechanisms Katherine Franz, Donita Brady, Martin Burke, Matteo Ceccarelli

• Stimuli-Responsive Materials for Therapy and Imaging Zijian Guo, Justin Wilson, Shuhei Furukawa, Zhuang Liu, Rachela Popovtzer, Anna Cristina Samia

• Targeted Metal-Based Therapeutics Thomas Meade, Seth Cohen, Maria Contel

• The GRC Power Hour™

Infections Andrew Darwin, Andrew Perault, Britney Hardy, Virginia Miller Victor Torres, Borden Lacy, Isaac Chiu, Jeongmin Song, John Mekalanos, Andreas Peschel

• Toxic Defense Mechanisms Peggy Cotter, Marek Basler, Christopher Hayes, Alecia Septer

• Subverting Host Functions with Bacterial Toxins and

Effectors Eric Skaar, Jim Cassat, Sophie Helaine, Ralph Isberg, ZhaoQing Luo, Asaf Levy

• Regulation of Genes and Proteins in Pathogens Raphael Valdivia, Petra Dersch, Aimee Shen, Joshua Woodward

Mitochondria and Chloroplasts Semi-Autonomous Organelles: From Fundamental Processes to Translation in Agriculture and Medicine JUL 17-22, 2022 MOUNT SNOW, WEST DOVER, VT CHAIR: Zach Adam VICE CHAIR: Antoni Barrientos

• Evolution and Dynamics of Organelles and Their Genomes Andreas Weber, Dan Mishmar, Dan Sloan

• Organelle Gene Expression Zofia Chrzanowska-Lightowlers, Alice Barkan, Brendan Battersby, Flavia Fontanesi, Meng Chen

• Protein Import, Sorting and Assembly Agnieszka Chacinska, Hsou-Min Li, Peter Rehling, Masato Nakai

• Organelle Dynamics: Division, Differentiation and Contacts Liza Pon, Yoshiki Nishimura, Maya Schuldiner, Samantha Lewis

• Structure and Function of Organelle Complexes Johannes Herrmann, Amandine Marechal, Alexey Amunts

• Organelle Metabolism Sabeeha Merchant, A. Harvey Millar, Veronica Maurino, Ken Nakamura

• Signaling and Stress Response Sally Mackenzie, Valentina Perissi, Jaakko Kangasjärvi

• Proteostasis, Mitophagy and Chlorophagy Klaas Van Wijk, Paul Jarvis, Hagai Abeliovich

• Organelle Biology Translated into Medicine and Agriculture Richard Hartley, Stephen Long, Giovanni Manfredi, Ralph Bock

• The GRC Power Hour™

• Intracellular Problems and Solutions Joanne Engel, Isabelle Derré, Marcia Goldberg, Rebecca Lamason, Renee Tsolis, Sarah Stanley

• Evolution of Virulence Factors Manuela Raffatellu, Ankur Dalia, Tamara O'Connor, Matthew Waldor

• Detection and Response to Bacterial Infections Russell Vance, Ivan Dikic, Katrin Mayer-Barber, Edward Miao, Anna Tischler, Sebastian Winter

Mitochondria and Chloroplasts Semi-Autonomous Organelles: From Fundamental Processes to Translation in Agriculture and Medicine JUL 16-17, 2022 CHAIRS: Florian Schober and Laura Klasek

• Keynote Session: Innate Sensing of Pathogens Kim Orth, Feng Shao

• The GRC Power Hour™ Drusilla Burns

Microbial Toxins and Pathogenicity Intercellular Interactions and Pathologic Outcomes JUL 9-10, 2022 CHAIRS: Britney Hardy and Andrew Perault

Molecular and Cellular Neurobiology Emerging Technologies to Study Nervous System Development, Function and Neurological Disease JUL 24-29, 2022 FOUR POINTS SHERATON, HOLIDAY INN EXPRESS, VENTURA, CA CHAIR: Aaron Gitler VICE CHAIR: Mingjie Zhang

• Keynote Session: Mechanisms of Neurological Disease Katja Brose, Carla Shatz, Viviana Gradinaru, Hailan Hu

• Development of the Nervous System Kang Shen, Shen-Ju Chou, Daniel Colón-Ramos, Gordon Fishell, Xuecai Ge, Yukiko Gotoh, Carina Hanashima, Melissa Rolls, Hongyan Wang

• Synapses and Synaptic Function Xiang Yu, Lu Chen, Camin Dean, Peter Scheiffele, Thomas Sudhof, Johannes Hell

• Neural Circuits and Behavior Shernaz Bamji, Anna Beyeler, Yang Dan, Steven Flavell, Nirao Shah, Juan Song, Yi Zuo

• Brain Imaging and Connectomics Yimin Zou, Na Ji, Tianyi Mao • Genetics and Epigenetics of the Nervous System Louis

• Molecular Interactions and Dynamics at Interfaces Jörg Meyer, Rainer Beck, Timothy Minton, Gilbert Nathanson, Alec Wodtke

• Impact of Machine Learning Philipp Marquetand, Roman Krems, Francesco Paesani, David Wilkins

• Photochemistry and Nonadiabatic Dynamics Michael Schuurman, Joseph Subotnik, David Yarkony, Kaijun Yuan, Benjamin Levine

Reichardt, Dan Geschwind, Nancy Ip, Bianca Marlin, Coleen Murphy, Theodore Price, Jie Shen

• Ultrafast Processes Xiaosong Li, Luis Banares, Marcos Dantus, Irene

• Sensory Systems John Ngai, Alexander Chesler, Sandeep Robert

• Molecular Interactions and Dynamics in Complex Systems

Datta, Craig Montell, Amita Sehgal, Fengwei Yu

• Mechanisms of Neurodegeneration and Regeneration Leonard Petrucelli, Frank Bradke, Jun Ding, Eric Huang, Martin Kampmann, Claire Le Pichon, James Shorter, Michael Ward

• Advanced Technologies for Neuroscience Research Yi Sun, Ryohei Yasuda, Feng Zhang

Jian Liu, Vicki Grassian, Wei Kong, Richard Loomis, Caroline Jarrold

• Keynote Session: Spectroscopy and Dynamics Ricardo Metz, Robert Field, Daniel Neumark, George Schatz

Molecular Interactions and Dynamics JUL 9-10, 2022

Molecular and Cellular Neurobiology Functional Integration of Neural Mechanisms in Health and Disease JUL 23-24, 2022 CHAIRS: Nicole Leung and Zacharie Taoufiq

Molecular Basis of Microbial One-Carbon Metabolism Enzymes and Metabolisms Driving the Global Carbon Cycle AUG 7-12, 2022 SOUTHBRIDGE HOTEL & CONFERENCE CENTER, SOUTHBRIDGE, MA CHAIR: Seigo Shima VICE CHAIR: Christopher Marx

• Methane and the Carbon Cycle Thomas Hanson, Justin North, Andrew Crombie, William Metcalf

• Biochemistry and Physiology of Aerobic Methylotrophy Yasuyoshi Sakai, Amy Rosenzweig, Alexander Tveit, Marina Kalyuzhnaya, Matthias Steiger

• Chemoautotrophy and Electrons Amelia-Elena Rotaru, Chris Greening, Bonnie Murphy, Nikhil Malvankar

• From C1 to C2: Acetogens, Reactions and Applications Mirko Basen, Volker Mueller, Byung-Kwan Cho, Stephen Ragsdale, Hannah Shafaat, Michael Koepke

• Ecology and Evolution of C1 Metabolism Kathleen Scott, Samantha Joye, Guillaume Borrel, Stephane Vuilleumier

• CO2 Fixation and Photorespiration Tobias Erb, Cheryl Kerfeld, Manajit Hayer-Hartl, Elke Dittmann, Elizaveta Bonch-Osmolovskaya

• Key Enzymes of Anaerobic C1 Metabolism Silvan Scheller, Gerrit Schut, Florin Musat, Jan Schuller

CHAIR: Matthew Bain

Molecular Structure Elucidation Recent Advances in Analytical Technologies to Expedite the Development of New Drug Modalities JUL 31-AUG 5, 2022 JORDAN HOTEL AT SUNDAY RIVER, NEWRY, ME CHAIRS: Mohammad Al-Sayah and R. Graham Cooks VICE CHAIRS: Yongchao Su and Gaurav Chopra

• Keynote Session: Discovery and Development of New Drug

Modalities Roy Helmy, Paul Carter, David Brayden • Analytical Characterization of New Drug Modalities Alexey Makarov, Wendy Sandoval, Rainer Fischer, Martin Gilar

• High Throughput Experimentation, Computational Chemistry

and Machine Learning Michael Wleklinski, Spencer Dreher • Advances in Spectroscopic Techniques Eric Munson, Qi Gao, Mei Hong, Krishna Mallela, Zheng Ouyang

• Emerging Techniques in Separation Science Samuel Yang, Robert Kennedy, Peter Shoenmakers, Kevin Schug

• Advancing Pharmaceutical Discovery and Development

Through Molecular Structure Elucidation Naijun Wu, Caroline McGregor, Huijuan Li, John Masucci

Cecilia Martinez-Gomez, Takuro Nunoura, Diana Sousa Liebeke, Anja Spang, Hiroyuki Imachi

• The GRC Power Hour

™

Cornelia Welte

Molecular Basis of Microbial One-Carbon Metabolism Microbial One-Carbon Conversion from the Microscale to the Global Scale AUG 6-7, 2022 CHAIRS: Marie Schölmerich and Grayson Chadwick

Nemes, Xin Yan, David Wishart

• Proteins in Unusual States David Russell, Vicki Wysocki, David Clemmer, Jennifer Brodbelt, Arthur Laganowsky, Michael Marty

• Efficient Development of Novel Analytical Technologies via

Collaborations Between Academia and the Pharmaceutical Industry Christopher Welch, Andreas Kaerner, Rebecca Whelan, Paul Bohn, Yong Liu

• The GRC Power Hour™

Multiferroic and Magnetoelectric Materials JUL 31-AUG 5, 2022 BATES COLLEGE, LEWISTON, ME CHAIRS: Venkatraman Gopalan and Ramamoorthy Ramesh VICE CHAIR: Tsuyoshi Kimura

• User Facilities for Materials Synthesis and Probes of

Fundamental Phenomena Padraic Shafer, Alan Tennant, John Freeland, Gerrit Vander Laan, Aaron Lindenberg

• Theoretical Frameworks and Machine Learning

Approaches Jorge Iniguez, Javier Junquera, Alexander Balatsky, Long-Qing Chen, Geoffroy Hautier

Molecular Interactions and Dynamics Dynamics and Spectroscopy of Chemical Systems JUL 10-15, 2022 STONEHILL COLLEGE, EASTON, MA CHAIR: Hua Guo VICE CHAIR: Ricardo Metz

• Cold and Ultracold Collisions and Reactions Andreas Osterwalder, Nandini Mukherjee, Balakrishnan Naduvalath, Edvardas Narevicius

• Molecular Interactions and Collisions in the Gas Phase Jun Li, Richard Dawes, Uwe Manthe, Arthur Suits, Roland Wester

• Kinetics of Combustion, Atmospheric and Interstellar Reactions David Osborn, Stephen Klippenstein, Marsha Lester, Albert Viggiano

Fiebig, Shinichiro Seki, Sang-Wook Cheong, Yoshinori Onose, Jirka Hlinka

• Keynote Session: Fundamental and Applied Science of

Multiferroics Sang-Wook Cheong, Ian Young, Jean-Marc Triscone, Darrell Schlom, Ekhard Salje • The GRC Power Hour™

Multiferroic and Magnetoelectric Materials Multiferroic Coupling Effects and Dynamics of Domains and Domain Walls at the Nanoscale JUL 30-31, 2022 CHAIRS: Mads Weber and Johanna Nordlander

Multiphoton Processes Fundamental Electronic and Structural Dynamics JUN 12-17, 2022 BRYANT UNIVERSITY, SMITHFIELD, RI CHAIR: Caterina Vozzi VICE CHAIRS: Nirit Dudovich and Daniel Rolles

• Keynote Session: Multiphoton Processes Marc Vrakking, Donna Strickland

• Chirality Markus Ilchen, Valerie Blanchet, Olga Smirnova, Oren Cohen • Electronic and Nuclear Dynamics in Complex Systems Adam Kirrander, Matthias Kling, Zhi Heng Loh

• Solid-State Dynamics Hadas Soifer, Jens Biegert, Ursula Keller, Mette Gaarde

• Nonlinear XUV and X-Ray Science Johan Mauritsson, James Cryan, Mizuho Fushitani

• Multidimensional Imaging of Chemical Dynamics Maria Novella Piancastelli, Till Jahnke, Itzik Ben-Itzhak, Albert Stolow

• Dynamics at Conical Intersections Russell Minns, Heide Ibrahim, Michael Schuurman

• Attosecond Dynamics Jonathan Marangos, Francesca Calegari, Paul Corkum, Alicia Palacios

• Emerging Techniques Michael Chini, Giulia Mancini, Jochen Mikosch

• The GRC Power Hour™ Valerie Blanchet, Nirit Dudovich

• The Dark Metabolome and Lipidome Christina Ferreira, Peter

• C1 Metabolism and Physiology Cornelia Welte, Masaru Nobu, N. • Syntrophy and Eukaryogenesis Colleen Cavanaugh, Manuel

Phenomena: Real Space and Reciprocal-Space Manfred

Burghardt

Reactions, Collisions and Energy Transfer on Short to Long Timescales

• The GRC Power Hour™

• Symmetry, Topology, Non-Reciprocal and Emergent

• Multiferroic Crystal Synthesis Tsuyoshi Kimura, Ram Seshadri, Shenqiang Ren, Vivien Zapf

• Thin Films, Heterostructures and Nanostructures Lane Martin, Chang-Beom Eom, Chan-Ho Yang, Pu Yu, Susan Trolier-McKinstry, Susanne Stemmer

• Applications of Multiferroics and Magnetoelectrics Cheng Song, Nian Sun, Geoffrey Beach, Cewen Nan, YinHao Chu

• Picoscale Metrology Xiaoqing Pan, Manfred Fiebig, Jan Musfeldt, Jan Seidel, Margaret Murnane

• Quantum Materials and 2-Dimensional Multiferroics Ni Ni, Zhiqiang Mao, Arzhang Ardavan, Xiaodong Xu, Youtarou Takahashi

Multiphoton Processes Study of Dynamics by Light-Matter Interaction: From Atoms to Complex Systems JUN 11-12, 2022 CHAIRS: Ruaridh Forbes and Omer Kneller

Multiscale Mechanochemistry NEW! and Mechanobiology From Molecular Mechanics to Smart Materials JUL 31-AUG 5, 2022 VENTURA BEACH MARRIOTT, VENTURA, CA CHAIR: Matthew Harrington VICE CHAIR: Kerstin Blank

• Multiscale Mechanics of Biological and Synthetic Materials Hermann Gaub, Viola Vogel, Stephen Craig

• Mechanosensing in the Different Domains of Life Viola Vogel, Anja Geitmann, Vernita Gordon, Alex Dunn

• Mechanically Induced Chemical Reactions Nancy Sottos, Evelina Colacino, Robert Göstl

• Mechanoresponsive Polymeric Materials Julia Kalow, Yi Cao, Andreas Walther

• Simulations and Mechanisms of Mechanoresponsive

Molecules Anna Tarakanova, Frauke Gräter, Jennifer Schwarz • Bottom-up Design of Mechanoresponsive Materials Niels Holten-Andersen, Gijsje Koenderink, Oren Scherman, Anna Rising

• Active Force Generation in Synthetic Systems Robert Göstl, Aranzazu Del Campo, Stephen Schrettl

• Bio-inspired Materials Phillip Messersmith, Douglas Fudge, Andre Studart

• Multiscale Methods for Measuring and Applying Forces Andreas Walther, Costantino Creton, Khalid Salaita

Multiscale Plant Vascular Biology

Mutagenesis

Assessing Plant Vascular Function Through Optical Approaches

Fundamental Mechanisms of Genomic Change and Adaptation

JUN 5-10, 2022 JORDAN HOTEL AT SUNDAY RIVER, NEWRY, ME CHAIRS: Brent Helliker and Jeannine Cavender-Bares VICE CHAIRS: Anna Sala and Rachel Spicer

JUN 12-17, 2022 JORDAN HOTEL AT SUNDAY RIVER, NEWRY, ME CHAIR: Julian Sale VICE CHAIR: Houra Merrikh

• Keynote Session: Viewing Plant Vascular Function Across

• Keynote Session: Fundamental Mechanisms of

Scales Noel Holbrook, Abigail Swann • Plant-Atmosphere Connections from Landscapes to Whole

Earth Yanlan Liu, Kyla Dahlin, Susan Ustin, Kim Novick • Water Movement Through Leaves to Ecosystems Yakir Preisler, Abraham Stroock, Andrew Leakey

• 3D Elucidation of Leaf Structure and Function Lawren Sack, Margaret Barbour, Craig Brodersen, Christine Scoffoni

• Vascular Transport from Whole Plants to

Ecosystems Clarissa Fontes, Kim O'Keefe, Anna Trugman • Xylem Structure-Function Relationships Francesca Secchi, Jochen Schenk, Jose Torres-Ruiz, Maciej Zwieniecki

• Phloem Structure-Function Relationships Jozica Gricar, Jessica Savage, Sanna Sevanto

• Stomatal and Aquaporin Mediated Water Flux Tom Buckley, Tim Brodribb, Menachem Moshelion

• Evolution of Plant Vascular Systems Adam Roddy, Charles Boyce, Monica Carvalho

• The GRC Power Hour™

Mutagenesis Daniel Jarosz, Sue Jinks-Robertson, Reuben Harris • DNA Damage Tolerance by the Replication Fork Sarah Lambert, Helle Ulrich, Susan Lovett, Wei Yang, Dana Branzei

• Visualizing Mutagenic Mechanisms Wei Yang, Joseph Loparo, Antoine Van Oijen, David Rueda

• Mutagenesis Arising from Replication Errors Susan Lovett, Thomas Kunkel, Roger Woodgate, David Pellman

• RNA-Dependent Mutagenesis Thomas Kunkel, Karlene Cimprich, Andres Aguilera, Hannah Klein

• Repeat and Barrier-Induced Mutagenesis Hannah Klein, Marcel Tijsterman, Catherine Freudenreich, Sarah Lambert, Sergei Mirkin

• Understanding Mutation Signatures in Cancer and

Aging K.J. Patel, Nuria Lopez-Bigas, Ruben van Boxtel • Environmental and Endogenous Mutagenesis Reuben Harris, Ivan Matic, K.J. Patel, Bjoern Schwer, Shana Sturla

• Evolvability and Adaptation Houra Merrikh, Lilach Hadany, Melissa Gymrek, Daniel Jarosz

• The GRC Power Hour™

Nanoscale Science and Engineering for Agriculture and Food Systems Convergence of Nanotechnology With Food and Agriculture JUN 19-24, 2022 SOUTHERN NEW HAMPSHIRE UNIVERSITY, MANCHESTER, NH CHAIRS: Antje Baeumner and Julie Goddard VICE CHAIRS: Carmen Gomes and Melanie Kah

• Keynote Session: Convergence of Nanotechnology with

Food and Agriculture Jason White, Sharon Walker, Fabio Pulizzi • Advances in Nanomaterials Margaret Frey, Brenda Hutton-Prager, Khara Grieger, Tony McNally

• Translation of Nano-Based Science for Application in Food

and Agriculture Timothy Duncan, Nick Dokoozlian, Marie Connett, Rick Shang

• Nanobiosensor Approaches to Improving Human and

Animal Health Man Bock Gu, Susana Campuzano Ruiz, Jenny Emneus, Sundaram Gunasekaran

• Environmental Nanotechnology Greg Lowry, Leonardo Fraceto, Rebecca Klaper

• Big Data in Food and Agricultural Nanotechnology: IoT and

Predictive Modeling Arturo Keller, Amalia Turner, Riccardo Accolla, Abigail Horn

• Nanodelivery Approaches to Improving Human and Animal

Health Gretchen Mahler, Debora Rodrigues, Ja-an Ho • Nanotechnology's Impact on Food Safety Richard Canady, Evangelyn C. Alocilja, Eric McLamore, Maya Al Sid Cheikh

Multiscale Plant Vascular Biology

Mutagenesis

• Nanotechnology's Role in Agriculture David Britt, Maria

Challenges for Plant Vascular Function in the Anthropocene

Mechanisms of Mutagenesis and Clinical Implications

• The GRC Power Hour™ Carmen Gomes, Melanie Kah

JUN 4-5, 2022

JUN 11-12, 2022

CHAIRS: Gerard Sapes and William Hammond

CHAIRS: Claudia Aloisi and Brandon Case

Musculoskeletal Biology and Bioengineering New Approaches to Accelerate Discovery in the Musculoskeletal System AUG 7-12, 2022 PROCTOR ACADEMY, ANDOVER, NH CHAIR: Tamara Alliston VICE CHAIR: Louis DeFrate

• Keynote Session: Biology and Bioengineering as a Platform

for Change Constance Chu, Kelly Stevens, Izzy Jayasinghe • Biology and Bioengineering of Aging in the

Musculoskeletal System Samuel Ward, Thomas Rando, Kharma Foucher, Sarah Dallas, Adetola Adesida

• Musculoskeletal Pain: Causes and Cures Anne-Marie Malfait, A. Vania Apkarian, Tony Yaksh, Gregory Hicks

• Spatial Context in the Musculoskeletal System Catherine Kuo, Lin Han, Ralph Müller, Stefano Di Talia, Alessandra Sacco

• Tracking Musculoskeletal Histories Over Time Ivo Kalajzic, Terence Capellini, Qing-Jun Meng, George Muschler

• Multiscale Metabolism in Musculoskeletal Tissue Crosstalk Peter Croucher, Ronald June, Nancy Lane, Tri Phan, Graham Williams

• Enlisting the Immune System for Musculoskeletal

Health Laura McCabe, Dana Graves, Danièle Noël, Hiroshi Takayanagi • Multiscale Musculoskeletal Mechanobiology Pen-Hsiu Chao, Belinda Beck, Melissa Knothe Tate, Alayna Loiselle, Elise Morgan

• Synthetic Musculoskeletal Biology and Biomaterial Alan Grodzinsky, Robert Bowles, Blanka Sharma, Johnna Temenoff

• The GRC Power Hour™

Myelin Translational Science of Myelin: From Glial Biology to Repair MAY 22-27, 2022 RENAISSANCE TUSCANY IL CIOCCO, LUCCA (BARGA), ITALY CHAIRS: Catherine Lubetzki and Kelly Monk VICE CHAIRS: Terri Wood and Jonah Chan

• Remyelination in Multiple Sclerosis and Animal

Models Anne Baron-Van Evercooren, Jonah Chan, Christine Stadelmann-Nessler, Benedetta Bodini, Robin Franklin

• Cell-Cell Interactions in Myelination Charles ffrench-Constant, Terri Wood, Sophie Belin, Peter Brophy, Julia Edgar, Jun Hee Kim, Eva-Maria Kramer-Albers, Elior Peles, Keiichiro Susuki, Anne Desmazieres

• Oligodendroglial Heterogeneity Bernard Zalc, Wendy Macklin, Goncalo Castelo-Branco, Vahbiz Jokhi, Ragnhildur Karadottir

• Novel Imaging Tools: From Cells to Human Tissue David Lyons, Bruno Stankoff, Martina Absinta, Emmanuel Beaurepaire, Jaime Grutzendler, Heidi Johansen-Berg, Dies Meijer, Peter Stys, Ethan Hughes

• Schwann Cell Development and Repair Laura Feltri, James Salzer, Peter Arthur-Farraj, Lydia Daboussi, Claire Jacob, Alison Lloyd, Piotr Topilko

• Development of Myelinating Glia Leda Dimou, Bruce Appel, Fiona Doetsch, Hyun Kyoung Lee, Jayshree Samanta, Ruth Stassart, Brad Zuchero

• Multiple Sclerosis: A Therapeutic Perspective Marco Salvetti, Frauke Zipp, Riley Bove, Jeremy Chataway, Gianvito Martino, Mariapia Sormani, V. Wee Yong

• Innate Immune Cells in Myelin Damage and Repair Roberta Magliozzi, William Talbot, Robert Hill, Inge Huitinga, Hans Lassmann, Veronique Miron, Marco Prinz, Sebastian Werneburg

Musculoskeletal Biology and Bioengineering

• Adaptive Myelination and Remyelination Maria Cecilia Angulo,

Multi-Scale Approaches to Understanding Musculoskeletal Tissues

• The GRC Power Hour™ Jennifer Orthmann-Murphy, Violetta Zujovic

AUG 6-7, 2022 CHAIRS: Sun Peck and Stefaan Verbruggen

Tobias Merson, Dwight Bergles, Maarten Kole, Letizia Leocani

Myelin Dynamics of Myelin Formation, Function and Repair MAY 21-22, 2022 CHAIRS: Meng-meng Fu and Jenea Bin

DeRosa, Raymond Briñas

Nanoscale Science and Engineering for Agriculture and Food Systems Convergence of Nanotechnology with Food and Agriculture JUN 18-19, 2022 CHAIRS: Ying Wang and Antonia-Teodora Perju

Nasopharyngeal Carcinoma Nasopharyngeal Carcinoma and Beyond: Lessons and Learnings from Virus-Associated Carcinomas MAY 8-13, 2022 REY DON JAIME GRAND HOTEL, CASTELLDEFELS, SPAIN CHAIRS: Kwok Wai Lo and Quynh-Thu Le VICE CHAIRS: Mu Sheng Zeng and Alan Chiang

• Keynote Session: Viruses and Tumor Development Lawrence Young, Joan Steitz, Ian Frazer

• Cancer Virus as a Target for Therapy and Vaccination HenriJacques Delecluse, Paul Lieberman, A. Dimitrios Colevas, Ka-Leung Wong, Jeffrey Cohen, Christian Ottensmeier, Stuart Wong

• Preclinical Models for NPC and OPC Kathy Ho Yen Shair, Christian Münz, Anna Chi Man Tsang, John Sunwoo

• Biomarkers for NPC and OPC Wei-Hua Jia, Christine Chung, Allan Hildesheim, Miao Xu, Anna Coghill, Maura Gillison, Benjamin Pinsky, Scott Bratman

• Translating Genomics to the Clinics: Therapeutic Perspective Maria Lung, Jin-Xin Bei, Vivian Wai Yan Lui, Robert West

• Tumor Microenvironment of NPC and OPC Pierre Busson, Rajiv Khanna, Robert Ferris, Qian Zhong, Xin-Yuan Guan

• Advances in Imaging, Pathology, Treatment Planning and

Clinical Management Sue Yom, Nasir M. Rajpoot, Jun Ma, Matt Lechner

• Immunotherapy in NPC and OPC Alan Rickinson, Barbara Burtness, Brigette Ma, Han Chong Toh, Rafi Ahmed

• Keynote Session: Future Perspectives in NPC Research and

Treatment Fei-Fei Liu, Charles Swanton, Garry Nolan • The GRC Power Hour™ Brigette Ma, Kathy Ho Yen Shair

NEW!

Natural Products and Bioactive Compounds

Neural Mechanisms of Acoustic Communication

The Function of Natural Products at the Interface of Chemistry and Biology

Circuits and Specializations for Behavioral Interactions in Acoustic Communication

JUL 31-AUG 5, 2022 PROCTOR ACADEMY, ANDOVER, NH CHAIR: Amber Onorato VICE CHAIR: Philip Kym

JUL 31-AUG 5, 2022 MOUNT HOLYOKE COLLEGE, SOUTH HADLEY, MA CHAIRS: Sarah Woolley and Michael Long VICE CHAIRS: Mala Murthy and Marc Schmidt

• Keynote Session: Biomimetic Inspired Synthesis of Natural

• Quantitative Approaches to Behavioral Analysis Jan

Products Jonathan Scheerer, Hosea Nelson, Richmond Sarpong, Dirk Trauner

• Innovative Chemical and Biological Technology Cheryl Hayward, Francis Gosselin, Lisa Marcaurelle, Derek Tan, Michael VanNieuwenhze

• Chemical Biology of Natural Products and Bioactive

Compounds Ryan Rafferty, Amanda Garner, Janet Smith, Gavin Williams

• Novel Synthetic Strategies and Methodology John D'Angelo, Mark Rizzacasa, Uttam Tambar, Tehshik Yoon

• Unique Methods for the Discovery of Natural

Products Katie Garber, Ikuro Abe, Tadeusz Molinski • Medicinal Chemistry of Natural Products and Bioactive

Compounds Carlos Zepeda, David Myles, David Limburg, Jamie McCabe Dunn

• Discovery and Biological Activity of Natural Products Jeremy Cody, Cassandra Quave, Chambers Hughes, Jon Thorson

• Chemical Modifications and Biological Activity of Natural

Products Kyle Rugg, Gregory Dudley, James Leahy, Daniel Appella • Keynote Session: Pioneering Synthetic Efforts Michael

Clemens, Roian Egnor, Catherine Perrodin, Coen Elemans

• Vocal Development Jon Sakata, Daniel Takahashi, Alison Barker, Michale Fee, Patricia Kuhl

• Models of Vocal Learning and Production Adrienne Fairhall, Jason Bohland, Ana Amador, Richard Hahnloser

• Auditory Specializations for Communication Ioana Carcea, Sarah Woolley, Todd Roberts, Lizabeth Marie Romanski, Robert Liu

• Vocal Interactions Xiaoqin Wang, Yossi Yovel, Arkarup Banerjee, Ofer Tchernichovski

• Genetics of Communication Constance Scharff, Genevieve Konopka, Hopi Hoekstra, Kate Watkins, Erich Jarvis

• Predictive Coding in Vocal-Motor Networks Andrew Bass, Vincent Gracco, David Schneider, Berthold Hedwig

• Comparative Anatomy and Function of Communication

Circuits Darcy Kelley, Anne Von Philipsborn, Benjamin Judkewitz, Mimi Kao, Lisa Stowers • Cortical Mechanisms of Vocal Production Daniela Vallentin, Michael Brainard, Steffen Hage, Edward Chang

• The GRC Power Hour™

Schmidt, Margaret Brimble, David Williams

• The GRC Power Hour™ Jamie McCabe Dunn, Cheryl Hayward

Natural Products and Bioactive Compounds Novel Approaches in Drug Discovery, Synthesis and Biosynthesis of Biological Relevant Natural Products JUL 30-31, 2022 CHAIRS: Bernhard Kepplinger and Gina Morgan

Neural Development Building the Nervous System: Insights from Development, Evolution and Disease AUG 7-12, 2022 SALVE REGINA UNIVERSITY, NEWPORT, RI CHAIR: Claude Desplan VICE CHAIR: Debby Silver

• Keynote Session: Principles of Neurogenesis Rosalind Segal, Fiona Doetsch, Magdalena Goetz, Catarina Homem

• Neural Cell Fate Specification Fiona Doetsch, Laure Bally-Cuif, Yukiko Gotoh, Bassem Hassan, Alessandra Pierani, Shubha Tole

• The Generation of Neural Diversity Yukiko Gotoh, Stavros Lomvardas, Song-Hai Shi, Josh Huang

• Neural Lineages: From Genomics to Imaging Laure Bally-Cuif, Zhirong Bao, Simon Hippenmeyer, Rick Livesey, Christian Mayer, Chris Doe

• Evolution of Brain Development Zhirong Bao, Detlev Arendt, Victor Borrell, Alejandro Sanchez Alvarado, Maria Tosches

Neurobiology of Brain Disorders Fundamental Mechanisms Leading to Novel Therapeutics and Biomarkers for Neurodegenerative Disease

• Function of Glia in Development Samantha Butler, Vilaiwan Fernandes, Maxwell Heiman, Cody Smith, Dong Yan

• Development of Neural Circuitry Cody Smith, Yishi Jin, Genevieve Konopka, Richard Mann, Niels Ringstad, Claire Wyart Konopka, Arturo Alvarez-Buylla, Flora Vaccarino, Giorgia Quadrato

Neural Development

Circuits of Cognition Christopher Harvey, Denise Cai, Jessica Cardin, John Maunsell, Jude Mitchell

• Neurophysiology of Human Cognition Rony Paz, Randolph Helfrich, Robert Knight, Lila Davachi

• Neural Mechanisms of Memory Tatiana Pasternak, Christos Constantinidis, Earl Miller, Anna Schapiro

• Motor Cognition Charles Schroeder, Michele Basso, Mark Churchland, Karel Svoboda

• Neural Encoding: Convergence and Controversy Stephanie Palmer, Brent Doiron, Ila Fiete, Stefano Fusi, Jennifer Groh

• Cognitive Maps Talia Konkle, Danielle Bassett, Elizabeth Buffalo, Sylvia Wirth

• The GRC Power Hour™ Sabine Kastner, Joni Wallis

Neurobiology of Cognition Multidisciplinary Approaches to Understanding the Neural Circuits of Cognition JUL 23-24, 2022 CHAIRS: Raman Saggu and Sebastien Tremblay

Neurobiology of Drug Addiction Addiction Research: From Molecules to Circuits to Treatment AUG 14-19, 2022 GRAND SUMMIT HOTEL AT SUNDAY RIVER, NEWRY, ME CHAIRS: Yavin Shaham and Marina Wolf VICE CHAIRS: Marina Picciotto and Serge Ahmed

• Keynote Session: Advances in Epigenetic and Circuit

Mechanisms of Drug Addiction: Implications to Treatment Pier Vincenzo Piazza, Eric Nestler, Nora Volkow

• Keynote Session: Development of Novel Blood-Based

• Learning Mechanisms of Drug Addiction Karen Ersche, Rita

Biomarkers for Neurodegenerative Disease Karen Duff, Chris Shaw, Henrik Zetterberg

• Genetic and Genomic Approaches to Neurodegenerative

Disease Carlos Cruchaga, Henne Vrei, Sonja Scholz, Peter Heutink, Hemali Phatnani

• Epigenetics of Neurodegenerative Disease Bess Frost, Christopher Glass, Sam Sisodia, Leslie Thompson, Anne Schaefer

• Frontotemporal Dementia and ALS: Mechanisms Benjamin

Pain Cecilia Flores, Brigitte Kieffer, Laura Bohn, Stefan Schulz, Nurulain Zaveri, Gregory Scherrer Fuchs, Geoffrey Schoenbaum, Regina Carelli, Stephanie Groman

• Synaptic Mechanisms of Drug Addiction Paul Kenny, Yan Dong, Kasia Radwanska, Vincent Pascoli, Carrie Ferrario, Meaghan Creed, Cassandra Gipson-Reichardt

• Addiction Theories Rita Goldstein, David Epstein, Jane Taylor, Lee Hogarth, Diana Martinez

• Animal Models of Drug Addiction and Relapse Gavan McNally,

Wolozin, Dorothee Dormann, Mina Gouti, Aaron Gitler, Michael Ward

Olivier George, Michael Nader, Chris Pierce, Marco Venniro, Nathan Marchant, Morgan James, Erin Calipari

• Parkinson's Disease: Mechanisms Mark Cookson, Valina

• Translational Research in Drug Addiction Markus Heilig, Aldo

Dawson, Towfique Raj, Patrik Verstreken, Dario Alessi

• Alzheimer's Disease: Mechanisms Soyon Hong, Beth Stevens, Christian Haass, Mathew Blurton-Jones, Tara Spires-Jones

• Tauopathies: Mechanisms and Biomarkers Celeste Karch, David Holtzman, Li Gan, Sally Temple, Guojun Bu

• Biomarkers: Diagnoses and Theranostics Fanny Elahi, Magdalini Polymenidou, Nicholas Seyfried, Donna Wilcock, Tania Gendron

Badiani, Sandra Comer, Courtney Miller, Matt Banks, Hedy Kober

• Circuitry of Drug Addiction Marisela Morales, John Mantsch, Sara Jones, Kate Wassum, Nii Addy, Drew Kiraly, Kathryn Reissner

• New Imaging Methods to Visualize the Effect of Addictive

Drugs on the Brain Veronica Alvarez, Byungkook Lim, Lin Tian, Ream Al-Hasani, Seksiri Arttamangkul

• The GRC Power Hour™ Rajita Sinha, Dorit Ron

• Therapeutics Approaches Mercedes Prudencio, Eric McDade, Chris Henderson, Sarah DeVos, Beverly Davidson

Neurobiology of Drug Addiction

Neurobiology of Brain Disorders

Mechanisms Underlying Development and Persistence of Drug Addiction

Neurodegenerative Disease: From Molecular Mechanisms to Potential Therapies

AUG 13-14, 2022 CHAIRS: Sam Golden and Megan Fox

AUG 6-7, 2022 CHAIRS: Judith Houtman and Brian Lananna

Neurobiology of Cognition Neural Circuits, Dynamics and Computations of Cognition and Behavior

AUG 6-7, 2022

JUL 24-29, 2022 JORDAN HOTEL AT SUNDAY RIVER, NEWRY, ME CHAIRS: David Freedman and Sabine Kastner VICE CHAIRS: Joni Wallis and Aaron Batista

CHAIRS: Daniel Pederick and Stephanie Redmond

• Keynote Session: Attention and Working Memory Elisabeth

Building the Nervous System: Cell Diversity, Circuit Assembly and Disease

Wang, Tatiana Engel, Daniel Yamins, Joshua Tenenbaum

• Beyond the Microelectode: New Approaches for Probing

• Cellular and Circuit Mechanisms of Opioid Addiction and

• Keynote Session: Human Development and Disease Genevieve • The GRC Power Hour™

Briggs, Michael Halassa, Richard Krauzlis, Yuri Saalmann

• Cognitive Computations in Brains and Machines Xiao-Jing

AUG 7-12, 2022 REY DON JAIME GRAND HOTEL, CASTELLDEFELS, SPAIN CHAIRS: Leonard Petrucelli and Alison Goate VICE CHAIRS: Karen Duff and Chris Shaw

• Axon Generation and Degeneration Maria Tosches, Stephanie Gupton, Samantha Butler, Dietmar Schmucker, Rosalind Segal, Jessica Treisman

• Subcortical Contributions to Cognition Helen Barbas, Farran

Murray, Robert Desimone, Kia Nobre

New Antibacterial Discovery and Development Disruptive Antibiotics and Non-Antibiotic Therapies to Combat Drug-Resistant Bacterial Infections JUL 24-29, 2022 RENAISSANCE TUSCANY IL CIOCCO, LUCCA (BARGA), ITALY CHAIRS: Ruben Tommasi and Matthew Cooper VICE CHAIR: Peter Smith

• Keynote Session: Clinical and Pre-Clinical Successes and

Failure Modes in Antibiotic Development Heike Broetz-Oesterhelt, Steven Projan, Ryan Cirz

• Alternatives to Antibiotics Robert Hancock, Heike BroetzOesterhelt, Guilherme Castro, Benjamin Chan, Heather Fairhead, Victor Nizet

• Unraveling the Requirements for Drug Permeation and

Target Engagement Olga Lomovskaya, Helen Zgurskaya, Muriel Masi, David Six, Paul Hergenrother

• New Approaches to Antibacterial Hits and Leads Peter Smith, Sharookh Kapadia, Nawaz Khan, David Roper, Mark Blaskovich, Andrew Tomaras

• Advances in Enabling Diagnostics and PK/PD Alita Miller, Eric Stern, George Drusano, William Hope, Valerie Raymond-Schwartzmann

• Learning from Successes and Failures in Antibacterial

Lead Optimization Richard Lee, Thomas Durand-Reville, Claudia Zampaloni, Daniel Obrecht, Scott Hecker, Alastair Parkes

• Antibiotic Adjuvants Gerry Wright, Ana Rita Brochado, Eric Brown, Olga Lomovskaya, Christian Melander

• New Results from Clinical Studies Troy Lister, Angela Talley, Katherine Young, Alita Miller

• Models for Advancing Antibiotics Ursula Theuretzbacher, Daniel Berman, Matthew Todd, Seamus O'Brien, Richard Alm

• The GRC Power Hour

™

Heike Broetz-Oesterhelt, Alita Miller

New Antibacterial Discovery and Development Challenges and Innovative Approaches to Discover and Develop New Antibacterial Agents JUL 23-24, 2022 CHAIRS: Ashleigh Paparella and Haroon Mohammad

Noble Metal Nanoparticles Harnessing Designer Metal Nanostructures for Diverse Applications JUN 12-17, 2022 MOUNT HOLYOKE COLLEGE, SOUTH HADLEY, MA CHAIR: Sara Skrabalak VICE CHAIR: Gregory Hartland

• Keynote Session: Metal Nanostructure Design and

Application Catherine Murphy, Christy Haynes, Younan Xia • Spectroscopy and Microscopy Amanda Haes, Kenneth Knappenberger, David Masiello, Jennifer Dionne, Utkur Mirsaidov

• Plasmonics for Energy Conversion Marina Leite, Tamar Seideman, Matthew Sheldon, Christy Landes

• Synthesis of Designer Nanostructures Sen Zhang, Matthew Jones, Ki Tae Nam, Svetlana Neretina, Richard Tilley

• On the Nanoparticle Surface James Evans, Jill Millstone, Kristen Fichthorn, Ayman Karim

• Designer Catalysts Christina Li, Graeme Henkelman, Michelle Personick, Matteo Cargnello, Peng Chen

• Nanostructures for Diagnosis and Delivery Teri Odom, Xing Yi Ling, Somin Lee, Xiaohu Xia

• Assembly, Self-Organization and Reconfiguration of

Nanoparticles Laura Na Liu, Robert Macfarlane, Xingchen Ye, Michael Engel, Vivian Ferry

• Selected Poster Presentations Gregory Hartland, Jianping Xie

• Notch and Development Rachael Kuintzle, Roshana Thambyrajah, Carmen Birchmeier, Ertugrul Ozbudak, Francois Schweisguth

• Transcription, Epigenetics and Notch Anna Bigas, Sarah Bray, Robert Faryabi

• Notch, Cancer and Therapeutics Lucio Miele, Rumela Chakrabarti, Adolfo Ferrando, Frank Kuhnert, Rajwinder Lehal

• Notch and Liver Disease Sarah Bray, Emma Andersson, Stacey Huppert, Hamed Jafar-Nejad, Utpal Pajvani, David Piccoli, Christian Siebel

• Signaling Interactions and Modulations Daniel Lafkas, John Ngo, Wendy Gordon, Vincent Luca, David Sprinzak

• Late-Breaking Topics Raphael Kopan, Nathalie Labrecque, Daniel Lafkas, Marc Vooijs

• Blood and Vessels Irwin Bernstein, Anna Bigas, Ralf Adams, • The GRC Power Hour™

Notch Signaling in Development, Regeneration and Disease Mechanisms of Notch Signaling in Health and Disease JUL 16-17, 2022 CHAIRS: Rachael Kuintzle and Roshana Thambyrajah

NOX Family NADPH Oxidases NOX Enzymes from Host Defense to Cell Signaling and Metabolic Disease MAY 29-JUN 3, 2022 MOUNT SNOW, WEST DOVER, VT CHAIR: Albert Van Der Vliet VICE CHAIR: Marie Jose Stasia

• Keynote Session: The NOX Family in Host Defense and

Redox Biology William Nauseef, Karl-Heinz Krause, Rafael Radi • NOX Structure and Functional Regulation Susan Smith, Francesca Magnani, Ji Sun, Elizabeth Sweeny, David Thomas

• Novel Tools to Assess NOX Activity and Function Louise Hecker, Edward Chouchani, Hadley Sikes, Thomas Michel

• NOX in Infection, Immunology and Microbiome

Regulation Mary Dinauer, Ulla Knaus, Nathalie Grandvaux, Balazs Rada, Amy Hsu

• Biological Targets of NOX Biology: Peroxidases, Thiol

Proteins and Ion Channels Franck Fieschi, Miklós Geiszt, Ivan Bogeski, Takaaki Akaike

• NOX in Cellular Metabolism and Metabolic Disease Ajay Shah, Agnes Görlach, Roberto Di Maio, Rhian Touyz, Gerta Hoxhaj

• Cell and Organelle-Specific Actions of NOX Enzymes Francisco R. Laurindo, Vikas Anathy, Dongmin Kang, Ron Mittler

• NOX in Cell Differentiation and Stem Cell Function:

Implication for Cancer Biology Kathy Griendling, Gareth Thomas, Katrin Schröder, Anna Martner, Lucia Lopes

• NOX in Translation: Implications for Clinical

Application Patrick Pagano, Cristina Furdui, Victor Thannickal • The GRC Power Hour™ Susan Smith

NOX Family NADPH Oxidases Structure-Function Relationships of Noble Metal Nanomaterials from Design Principles to Diverse Applications

The Role of NOX-Dependent Oxidant Signaling in Health and Disease: Towards Therapeutic Targets MAY 28-29, 2022 CHAIRS: Dina Vara and Carmen Veith

Notch Signaling in Development, Regeneration and Disease Mechanisms of Notch Signaling in Health and Disease JUL 17-22, 2022 BATES COLLEGE, LEWISTON, ME CHAIRS: Ivan Maillard and Freddy Radtke VICE CHAIRS: Jon Aster and Kim Dale

• Keynote Session: Setting Notch in Context Jon Aster, Kim Dale, Kun-Liang Guan, Nancy Speck

• Structure and Mechanisms of Notch Activation John Ngo, Stephen Blacklow, Robert Haltiwanger, Penny Handford

Nunoura, Jianfang Chen

• Hydrocarbon Degradation in the Deep-Sea Sediments Fengping Wang, Zhongze Shao, Katherine Dawson

• Biogeochemistry in Polar High Latitude Oceans Wei-Jun Cai, Jianfang Chen, Patricia Matrai, Walter Geibert

• Shelf and Estuarine Biogeochemistry Under Anthropogenic

Stress Celia Marrase, Jianping Gan, Katja Fennel • Biogeochemistry in Ancient Oceans Sean Crowe, Ariel Anbar, Kikki (Helga) Flesche Kleiven, Eva Stueeken

• Current and Future Oceans Galen McKinley, Tim Lenton, Christopher Sabine

Ocean Biogeochemistry Biogeochemical Processes Across Space and Time APR 30-MAY 1, 2022 CHAIRS: Qian (Lydia) Li and Christian Lindemann

Ocean Global Change Biology Integrating Environmental, Organismal and Community Complexity into Ocean Global Change Research JUL 17-22, 2022 WATERVILLE VALLEY, WATERVILLE VALLEY, NH CHAIR: Sinead Collins VICE CHAIR: Mary Sewell

• Modeling Different Timescales in Ocean Change Biology Andy Ridgwell, Patricia Sanchez-Baracaldo, Ben Ward

• Horizon-Scanning in Ocean Global Change Biology Francis Chan, Victoria Coles, David Hutchins, Andreas Osclies

• Understanding the Role of Environmental Fluctuations in

Shaping Organismal Responses Luis-Miguel Chevin, Joanna Bernhardt, Juan Gaitan-Espitia, David Vasseur

• Epigenetics and Transgenerational Plasticity Naomi Levine, Melanie Heckwolf, Frank Johannes, Katie Lotterhos

• Organismal Interactions in Changing Oceans Paul Renaud, Corina Brussaard, Fernando Lima

• Tropicalization Chris Harley, Jason Hall-Spencer, Adriana Verges • Biological Variation and Responses to Changing

Environments C. Elisa Schaum, Amanda Bates, Colin Kremer, Tatiana Rynearson

• Life Histories and Ocean Change Mary Sewell, Catriona Clemmesen, Anke Kremp, Jonathan Havenhand

• Incorporating Conservation and Mitigation Goals into

Fundamental Research Gretchen Hofmann, Trisha Atwood, Philip Boyd

Ocean Global Change Biology Synthesizing Approaches to Predict Species Responses to Global Change JUL 16-17, 2022 CHAIRS: Mark Bitter and Matthew Sasaki

Ocean Mixing The Impact of Ocean Mixing on the Earth, Ocean and Atmosphere Systems, Climate and Society

Ocean Biogeochemistry

JUN 5-10, 2022 MOUNT HOLYOKE COLLEGE, SOUTH HADLEY, MA CHAIRS: Jonathan Nash and Kurt Polzin VICE CHAIRS: Sonya Legg and Alberto Naveira Garabato

Biogeochemical Processes Across Space and Time

• The Evolving Perspective of Ocean Mixing: Uncertainties in

MAY 1-6, 2022 REY DON JAIME GRAND HOTEL, CASTELLDEFELS, SPAIN CHAIRS: Chuanlun Zhang and Susanne Neuer VICE CHAIRS: Adina Paytan and Fei Chai

• Physics Near the Ice-Ocean Interface: Mixing in

JUN 11-12, 2022 CHAIRS: Melissa King and Stephen Lee

Organisms and Viruses Angelicque White, Xiao-Hua Zhang, Takuro

Julia Mack

• The GRC Power Hour™ Amanda Haes

Noble Metal Nanoparticles

• Carbon and Nitrogen Cycles Mediated by Keystone

• The Deoxygenation of the World Oceans Denise Breitburg, Ronnie Glud, Sunke Schmidtko

• Biological Carbon Pump and Microbial Carbon Pump in

Changing Oceans Nianzhi Jiao, Bethanie Edwards, Morten Iversen, Carol Robinson

• Particle Pumps: Role of Animals and Injections Sarah Fawcett, Herve Claustre, Santiago Hernandez De Leon

Global Predictions and Assessing Risk and Societal Impact in a Changing Climate Sjoerd Groeskamp, Julie Pullen, Angelique Melet

Ice-Influenced Oceans Mary-Louise Timmermans, Sylvia Cole, Tom Rippeth, Amelie Meyer

• Physics Near the Ice-Ocean Interface: Mixing Beneath Ice

Shelves, in Fjords and Near Sea Ice Satoshi Kimura, Claudia Cenedese, Bishakhdatta Gayen

• Mixing in the Interior: Internal Waves and the Next

Generation of Parameterizations Cynthia Bluteau, Alexis Kaminski, Friederike Pollmann, Giovanni Dematteis

• Upper-Ocean Mixing and Impacts on Biogeochemistry Peter Franks, Amala Mahadevan, Laure Resplandy

• Mesoscale and Submesoscale Processes: Eddies,

Eddy-Wave Interactions and Nonlinear Coupling Amit Tandon, Leah Johnson, Jennifer MacKinnon, Hideharu Sasaki

• Mixing and Its Role in Climate Dynamics Eleanor Frajka-Williams, Camille Lique, David Marshall, Andreas Schmittner

• Mixing at the Bottom Erika McPhee-Shaw, Ruth Musgrave, Jacob Wenegrat, Bethan Wynne-Cattanach

• Pathways to Reducing Uncertainty Matthew Alford, Tom Farrar, Eric D'Asaro

• The GRC Power Hour™ Alejandra Sanchez-Rios, Sally Warner

Ocean Mixing

• Computational Behavior Analysis Nadine Gogolla, Sandeep Robert Datta, Mackenzie Mathis, Mala Murthy

• Circuits for Reward, Motivation and Addiction Steve Ramirez, Kate Wassum, Paul Kenny, Zayd Khaliq, Veronica Alvarez, Erin Calipari, Christian Luscher

• Circuits in Action Vanessa Ruta, Adam Hantman, John Tuthill, Gaby Maimon

• Circuits for Social Behaviors Bianca Jones Marlin, Gul Dolen, Dayu Lin, Garret Stuber, Catherine Dulac, Ishmail Abdus-Saboor

• Seeing Voltage: Sensors and Imaging Christina Kim, Michael Lin, Luke Lavis

• Behold the Power of Light Yalan Xing, David Nicewicz, Abigail Doyle, Ryan Gilmour

• More C-C Bond Formation and Methods Michael Harmata, Hongli Bao, Thomas Snaddon

• Let the Chemistry Flow Silas Cook, Nadine Kuhl, Jessica Herrick, Jason Hein, Timothy Noel, Timothy Jamison

• Reactions in Motion Michael Zacuto, Robert Flowers, Oliver Kappe, Mary Russell

• Chemistry on Complex Molecules Craig Merlic, John Jasper, Lukas Goossen, Jeff Johnson

• The GRC Power Hour™ Jen Heemstra and Emma McInturff

• The GRC Power Hour™

Optogenetic Approaches to Understanding Neural Circuits and Behavior

Organometallic Chemistry

JUN 4-5, 2022

Expanding and Integrating Optogenetic Tools and Techniques

JUL 10-15, 2022 SALVE REGINA UNIVERSITY, NEWPORT, RI CHAIR: Mitch Smith VICE CHAIR: Heather Spinney

CHAIRS: Marion Alberty and Sjoerd Groeskamp

JUL 16-17, 2022

• Bioorganometallic Chemistry Paula Diaconescu, Joan Broderick,

Ocean Mixing from the Smallest to the Largest Scales and its Impact on Ocean Dynamics, Biogeochemistry and the Climate System

CHAIRS: Kevin Monk and Sarah Stern

Hannah Shafaat

• Late and Heavy Metal Chemistry Selvan Demir, Aaron Tondreau,

Optics and Photonics in Medicine and Biology

Organic Geochemistry

• Harnessing Photons and Electrons John Gordon, Louise

Biophotonics Spanning the BiologyMedicine Continuum

The Formation and Fate of Organic Matter: How It Regulated Earth History and Will Shape Its Future

• Synthesis and Catalysis with More Abundant Metals Aaron

JUL 10-15, 2022 BATES COLLEGE, LEWISTON, ME CHAIRS: Kristen Maitland and David Sampson VICE CHAIRS: E. Duco Jansen and Snow Tseng

JUL 31-AUG 5, 2022 HOLDERNESS SCHOOL, HOLDERNESS, NH CHAIR: Richard Pancost VICE CHAIR: Anna Martini

• Advanced Microscopy and Imaging Stephani Otte, Winfried

• The Limits of Our Understanding of Organic Matter Erdem

Denk, Jonathan Liu, Gabriel Popescu

• Label-Free Imaging Andrew Rollins, Yongkeun Park, Shalin Mehta, Kimani Toussaint, Irene Georgakoudi

• Engineering Contrast Afrouz Anderson, Cristina Zavaleta, Daniel Razansky, Summer Gibbs

• Margin Assessment and Surgical Guidance Sylvain Gioux, Laura Marcu, Muyinatu Bell, Christopher Contag

• Neuroscience and the Brain Anna Devor, Daniel Cote, Jana Kainerstorfer

• Imaging in the Circulatory System Charles Lin, Eva Sevick-Muraca, Darren Roblyer, Sarah Bohndiek, Clemens Alt

• Endoscopy Audrey Bowden, Caroline Boudoux, Eman Namati, Kev Dhaliwal • Noninvasive Probing of the Eye Ralf Brinkmann, Iwona Gorczynska, Kirill Larin, Peter Török, Gereon Huettmann

• Photo-Activation and Inactivation Alex Vitkin, Kaushal Rege, Bryan Spring, Vanderlei Bagnato

• The GRC Power Hour™ Caroline Boudoux, Irene Georgakoudi

Vincent Lavallo, Jennifer Schomaker

Idiz, Lena Vincent, Alon Amrani

• The Evolutionary and Geological History of Biosynthetic

and Metabolic Pathways Paula Welander, Jochen Brocks, Amanda Garcia, Sarah Hurley, Patrick Shih

• Interfaces Between Organic and Inorganic Chemistry:

Exploring the Role of Machine Learning in the Future of Biophotonics JUL 9-10, 2022 CHAIRS: Danielle Harper and Madeleine Durkee

Optogenetic Approaches to Understanding Neural Circuits and Behavior Linking Brain Circuits to Behavior: Novel Methods and Biological Insights Derived from Optogenetic Approaches JUL 17-22, 2022 GRAND SUMMIT HOTEL AT SUNDAY RIVER, NEWRY, ME CHAIR: Denise Cai VICE CHAIR: Ofer Yizhar

• Keynote Session: Neural Circuits and Neuromodulators in

Health and Disease Sheena Josselyn, Kay Tye, Lin Tian, Kafui Dzirasa • Circuits for Stress, Pain and Fear Conor Liston, Thomas Kash, Sheena Josselyn, Michael Bruchas, Joshua Gordon

• Seeing Dynamics and Understanding Circuits Joshua Trachtenberg, Na Ji, Yevgenia Kozorovitskiy, Daniel Aharoni

• Brain-Wide Dynamics Saskia de Vries, Karl Deisseroth, Anne Churchland, Kanaka Rajan, Yang Dan, Gina Poe

Sadow, Kyle Lancaster, Corinna Schindler

• Early-Career Investigator Presentations Thomas Cundari, Hosea Nelson, Neil Tomson, Jenny Yang

• Main Group Chemistry Nora Radu, Christopher Cummins, Stephen Westcott

• Organometallic Chemistry at Surfaces Odile Eisenstein, John Roberts, Matthew Conley, Christophe Coperet

• Bond Activation and Functionalization John Walzer, Robert Phipps, Matthew Sigman

Preservation, Destruction and Interactions Johan Weijers,

• Ligands and Metals Heather Spinney, R. Tom Baker, Paul Chirik

Prachi Joshi, Christian Maerz, Sander Van Den Boorn

• The GRC Power Hour™ Nancy Williams, Jenny Yang

• Lipid Membranes: From Biophysics to Adaptation to Novel

Proxies Nicole Bale, Florence Schubotz, Phil Oger, Laura Villanueva,

Organometallic Chemistry

Jiasong Fang, Guy Schleyer

Transition Metal and Main Group Synthesis and Catalysis for a Sustainable Future

• Big Data Approaches to Obtain New Understanding of

Geological Systems Jeff Sheremata, Krista Longnecker, Thomas Abraham, Yishu Song

JUL 9-10, 2022 CHAIRS: Natalia Loewen and Eric Cueny

• The Myriad Pools and Archives of OM Ryan Pereira, Asmeret Asefaw Berhe, Thomas Blattmann, Anja Engel, Peter Hernes

• The Organic Geochemistry of the Arctic Bart van Dongen, Lisa Bröder, Carolyn Ruppel, Rémi Amiraux

• Measuring and Deciphering Intramolecular Isotopes

Across Space and Time Kate Freeman, Alexis Gilbert, Barbara

Optics and Photonics in Medicine and Biology

Berben, Yogesh Surendranath, Daniel Nocera

Sherwood Lollar

• Late-Breaking Topics Elise Wilkes • The GRC Power Hour™ Nicole Bale, Richard Pancost

Oscillations and Dynamic Instabilities in Chemical Systems Nonequilibrium to Induce and Maintain Spatio-Temporal Patterns JUL 17-22, 2022 STONEHILL COLLEGE, EASTON, MA CHAIR: Satoshi Nakata VICE CHAIR: Marcus Hauser

Organic Geochemistry

• Spatio-Temporal Pattern Based on Reaction-Diffusion

Mechanistic and Experimental Insights on Geochemical Archives

• Self-Organized Active Matter Kouichi Asakura, Raymond Kapral,

JUL 30-31, 2022 CHAIRS: Elise Wilkes and Julie Lattaud

Organic Reactions and Processes

Systems Tomohiko Yamaguchi, Annette Taylor, Alberto Munuzuri Masaharu Nagayama, Lee Cronin

• Electrochemical Control on Oscillations and Patterns Katharina Krischer, Istvan Kiss, Ronald Imbihl

• Spatio-Temporal Collective Behaviors Hiroyuki Kitahata, Veronique Pimienta, Jeremie Palacci, Nobuhiko Suematsu, Hiraku Nishimor

Innovations in Synthesis: Advancing Capabilities and Empowering Industrial Processes

• Molecular Design of Self-Organized Structures John Pojman,

JUL 17-22, 2022 BRYANT UNIVERSITY, SMITHFIELD, RI CHAIRS: Sriram Naganathan and Jimmie Weaver VICE CHAIRS: Craig Merlic and Michael Zacuto

• Biological Oscillations and Patterns Takashi Amemiya,

• Stereochemical and Atomic Control in Organic

• Nonlinear Dynamics: Synchronization, Bifurcation and

Synthesis Mark Biscoe, Qiu Wang, David Lupton, Cathleen Crudden • Installation and Uses of Halogens Florence Williams, Rebecca Green, Mark Kerr, Megan Smyth, Tobias Ritter, Beate Koksch

• Innovative Strategies in C-C Bond Formation Erin Stache, Debabrata Maiti, Sarah Wengryniuk, Chulbom Lee

• Proteins and Similars Sebastien Laulhe, Emma McInturff, Jie Xu, Sara Bonderoff, Samuel Gellman, Jennifer Heemstra

Anna Balazs, Andreas Walther Geneviève Dupont, Takashi Miura

• Emergence in Signal Transduction and Network

Systems Toshiyuki Nakagaki, Castern Beta, Agota Toth Chaos Dezso Horvath, Irving Epstein, Anne De Wit, Sumana Dutta • Pattern Formation Coupled with Mass Transfer and

Flow Kenneth Showalter, Jerzy Gorecki, Oliver Steinbock

Oscillations and Dynamic Instabilities in Chemical Systems

Phosphorylation and G-Protein Mediated Signaling Networks

Looking at Science and Technology Through the Lens of Nonlinear Chemistry

Mechanisms in G-Protein and Kinase-Mediated Signaling

• Keynote Session: Symbioses Cara Haney, Maria Harrison, Giles Oldroyd

• Development in Space Madelaine Bartlett, Zach Lippman, Miltos Tsiantis, Minako Ueda

JUL 16-17, 2022

JUN 11-12, 2022

• Biotic Interactions Hua Lu, Hailing Jin, Sophien Kamoun

CHAIRS: Domenico Bullara and Pamela Knoll

CHAIR: Ankita Jaykumar

• RNA: Roles Beyond the Message Aman Husbands, Xiaofeng Cao, Blake Meyers

• Nutrient Regulation and Transport Terri Long, Rodrigo Gutierrez,

Personalized Medicine

Photonuclear Reactions

From Scientific Basis to Clinical Practice in Individuals and Populations

Frontiers in Nuclear and Hadronic Physics

• Development in Time Stacey Harmer, Hong Gil Nam, Mark Estelle

AUG 7-12, 2022 HOLDERNESS SCHOOL, HOLDERNESS, NH CHAIR: Huey-Wen Lin VICE CHAIRS: Douglas Higinbotham and Marc Vanderhaeghen

• Modeling and Gene Regulatory Networks Gabriel Krouk,

JUN 26-JUL 1, 2022 VENTURA BEACH MARRIOTT, VENTURA, CA CHAIRS: Hsing-Jien Kung and Pui-Yan Kwok VICE CHAIR: Dean Ho

• Genomic Profiling: Tools and Applications Robert Nussbaum, Nikolaus Schultz, Janina Jeff

• Precision Oncology: Early Detection Dan Robinson, Colin Collins, Muh-Hwa Yang, Donald Parsons

• Genomic Approaches to Rare Disease Diagnosis Ebony Madden, Sharon Plon, Stephen Kingsmore

• Personalized Oncology: Tailored Treatment-1 Emily Lin, Dan Robinson, Edward Chow, Victoria Seewaldt

• Social and Ethical Implications of Personalized

Medicine Fatima Munoz, Sara Ackerman, Mildred Cho • Personalized Oncology: Tailored Treatment-2 David Ann, Whei-Mei Teresa Fan, Kun-Liang Guan, Melanie McReynolds

• Genomic Approaches to Infectious Disease Diagnosis David Engelthaler, Charles Chiu, Alexander Greninger

• Common Disease Risk Prediction and Mitigation Kelly Frazer, Natasha Strande, Nancy Cox

• Personalized Medicine for Large Populations Ysabel Duron,

• New Results in Precision Hadron Structure with

Electromagnetic Probes Aldo Antognini, Sylvester Joosten, Nikolaos Sparveris

• Femtography of Hadrons Barbara Pasquini, Xiangdong Ji, Julie Roche • Electrons for Neutrinos Or Hen, Adi Ashkenazi, Afroditi Papadopoulou, Sam Zeller, Noemi Rocco

• Hadrons in the Nuclear Medium Eliezer Piasetzky, Efrain Segarra, Igor Korover, Gerald Miller, Ronen Weiss, Dien Nguyen

• Nuclear Precision Physics and Applications Concettina Sfienti, Chiara Mazzocchi, Saori Pastore

David Mendoza Cozatl

Martin Howard, Joseph Swift

• Environmental Sensing Ullas Pedmale, Julia Bailey-Serres, Dawn Nagel, Richard Vierstra

• Keynote Session: Gene and Genome Evolution Benjamin Blackman, Pamela Soltis, Jennifer Wisecaver

• The GRC Power Hour™ Stacey Harmer

Plant Molecular Biology Diversifying the Plant Molecular Biology Toolkit to Understand and Engineer Plants JUN 11-12, 2022 CHAIRS: Jennifer Brophy and Sunil Kumar Kenchanmane Raju

• Hadron Spectroscopy Annalisa D'Angelo, Justin Stevens • From QCD to Gravitational Waves Jocelyn Read, Jorge Piekarewicz, Kenta Kiuchi

Plasma Processing Science Plasmas and Their Interactions with Matter

• Nuclear Physics and Quantum Information Science Ian Cloet, Srimoyee Sen, Zohreh Davoudi

• Physics with an Electron Ion Collider Abhay Deshpande, Elena Long, Todd Satogata

JUL 24-29, 2022 PROCTOR ACADEMY, ANDOVER, NH CHAIR: Anthony Murphy VICE CHAIR: Lorenzo Mangolini

• The GRC Power Hour™ Huey-Wen Lin, Elena Long

• Measuring the Interplay between Plasma and Matter

Plant and Microbial Cytoskeleton

• Plasma Synthesis of Novel Materials Elijah Thimsen, Mohan

Personalized Medicine

Cytoskeletal Diversification Across the Domains of Life

• Linking Plasma Processing and Fusion Plasmas Yevgeny

Precision Oncology Highlighting Molecular Diagnostics and Experimental Therapeutics

AUG 14-19, 2022 PROCTOR ACADEMY, ANDOVER, NH CHAIRS: Erin Goley and Geoffrey Wasteneys VICE CHAIRS: Sophie Martin and Alexander Paredez

• Plasma Interactions with Biological Materials Greg Fridman,

• Keynote Session: Evolution of the Cytoskeleton Magdalena

• Complex Chemical Synthesis Using Plasmas Katharina

Alicia Zhou, Carlos Bustamante

• The GRC Power Hour™ Ebony Madden, Nancy Cox

JUN 25-26, 2022 CHAIRS: Chia-Lin Chen and Emine Gunes

Holger Kersten, Sedina Tsikata, David Pai

Bezanilla, Marko Kaksonen, Nina Salama

Phosphorylation and G-Protein Mediated Signaling Networks Molecular Mechanisms of Signal Integration in Cellular and Organismal Regulation JUN 12-17, 2022 SOUTHBRIDGE HOTEL & CONFERENCE CENTER, SOUTHBRIDGE, MA CHAIR: Rebecca Berdeaux VICE CHAIR: Alan Smrcka

• Keynote Session: Regulation of Protein Kinase Signaling Anton Bennett, Alexandra Newton, Robert Screaton, Yonghao Yu

• Membrane Proximal G-Protein Signaling Alan Smrcka, Heidi Hamm, Ku-Lung Hsu, Nevin Lambert, Angeline Lyon

• Cyclic Nucleotide Regulated Signaling Carmen Dessauer, Xiaodong Cheng, Lonny Levin, Susan Taylor

• G-Protein and Kinase Signaling in Physiological

Control Henrik Dohlman, Gregory Tall, Melanie Cobb, Carmen Dessauer,

• Proliferation and Reproduction Christopher de Graffenried, Alex Bisson, Rui Li, Simonetta Piatti, Carolyn Rasmussen

• Interactions with Membranes Anthony Vecchiarelli, Aoife Heaslip, Geraldine Laloux, Snezhka Oliferenko

• Wall Polymer Placement and Cell Morphogenesis Sabine Mueller, Chris Ambrose, Rut Carballido-Lopez, Nicolas Minc

• Selected Poster Presentations Prachee Avasthi • Cell Polarity and Polar Growth Daniel Lew, Michelle Facette, Shanjin Huang, Liedewij Laan, Luis Vidali

• Motors and Motility Lillian Fritz-Laylin, Ram Dixit, Freddy Frischknecht, Kent Hill

• Regulating Cytoskeletal Dynamics Marc Edwards, Bruce Goode, David Kovar, Alphée Michelot, Hiroyasu Motose

• Keynote Session: Host-Microbe Interactions Alexander Paredez, Dominique Soldati-Favre, Chris Staiger

• The GRC Power Hour

™

Kirill Martemyanov, Kendall Blumer, Evi Kostenis, Roger Sunahara

• GPCR-Activated Signaling in Control of Cell Proliferation

and Cancer Melanie Cobb, Antonio Amelio, Kun-Liang Guan, J. Silvio Gutkind, Michelle Kimple

• Integration of Phosphorylation and G-Protein Mediated

An Evolving Cytoskeleton: Diverging Mechanisms and Converging Patterns AUG 13-14, 2022 CHAIRS: Katrina Velle and Ryan Eng

Plant Molecular Biology Spatial and Temporal Dynamics in Plant Biology

Bennett, John Scott

JUN 12-17, 2022 HOLDERNESS SCHOOL, HOLDERNESS, NH CHAIR: C. Robertson McClung VICE CHAIR: Rebecca Mosher

Roger Sunahara, Arun Shukla, Stephen Sprang, John Tesmer

Stapelmann, Julia Bandow, Felipe Iza

• Plasmas and Catalysts Maria Carreon, William Schneider, Sankaran Sundaresan

• Plasma Surface Modification and Deposition Michael Gordon, Sumit Agarwal, Lenka Zajickova

• The Plasma-Liquid Interface Peter Bruggeman, Dingxin Liu, Fumiyoshi Tochikubo, Ester Marotta

• Plasmas for the Environment Sylvain Coulombe, Volker Hessel, Mariadriana Creatore

• The GRC Power Hour™

Plasma Processing Science Investigating Multiphase and Multiscale Plasma-Material Interactions JUL 23-24, 2022 CHAIRS: Judith Golda and Marien Simeni Simeni

Nanoscale Light-Matter Interactions for Sustainability JUL 10-15, 2022 GRAND SUMMIT HOTEL AT SUNDAY RIVER, NEWRY, ME CHAIR: Jennifer Dionne VICE CHAIR: Javier Aizpurua

• Keynote Session: Dynamic Light-Matter Interactions Nader

Signaling Joan Heller Brown, Roshanak Irannejad, Jurgen Wess, Anton • Keynote Session: Structural Aspects of G-Protein Signaling

Antoine Rousseau, Nevena Puac

Plasmonics and Nanophotonics Plant and Microbial Cytoskeleton

• Signaling Beyond the Plasma Membrane John Scott, Jeff Frost, Alan Jones, Carol Williams

Raitses, David Ruzic, Michael Campanell

Erin Goley, Geoffrey Wasteneys

Joan Heller Brown, Kirill Martemyanov

• Physiological and Chemical Regulation of G-Protein Activity

Sankaran, Scott Walton, Boris Feygelson

Engheta, Mark Brongersma, Peter Nordlander, Teri Odom

• Photochemistry and Catalysis Renee Frontiera, Peng Chen, Prashant Jain, Yousoo Kim, Christy Landes

• Sustainable Energy and the Environment Harry Atwater, Shanhui Fan, Vivian Ferry, Matthew Sheldon

• Nanophotonics for Biology and Medicine Laura Fabris, Rizia Bardhan, Gennady Shvets

• Metasurfaces and Metamaterials Jon Schuller, Andrea Alu, Jason Valentine

• RNA Localization and Assembly Douglas Black, Kimberly Mowry, Robin Stanley, Lingling Chen, Beatriz Fontoura

• Active Nanophotonics and Molecular-Scale Optoelectronics Carsten Rockstuhl, Joshua Caldwell, Jeremy Baumberg, Christian Nijhuis, Uriel Levy, Maiken Mikkelsen, Anatoly Zayats

• Quantum and Nonlinear Nanophotonics Aitzol Garcia-Etxarri, Yuri Kivshar, Prineha Narang, Timur Shegai, Francisco Garcia-Vidal

• RNP Function and Disease Implications Manuel Ares, Eric Wang, Sara Cherry, Kathryn Hamilton, Peter Sarnow, Adrian Krainer

• Integration of RNA Biogenesis Steps Nicholas Conrad, Tracy Johnson, Matthew Simon, David Bentley

• The GRC Power Hour™ Kristen Lynch, Karla Neugebauer

• Novel Syntheses and Spectroscopies Javier Garcia de Abajo, Bin Ren, Mathieu Kociak Naomi Halas, Vladimir Shalaev, Luat Vuong

• The GRC Power Hour

™

Teri Odom, Luat Vuong

Plasmonics and Nanophotonics Engineering Nanoscale Light-Matter Interactions for Energy, Communication and Biomedical Applications JUL 9-10, 2022 CHAIRS: Loza Tadesse and Pavlos Pachidis

Polymer Physics Polymer Physics for Sustainability JUL 24-29, 2022 MOUNT HOLYOKE COLLEGE, SOUTH HADLEY, MA CHAIR: Sanat Kumar VICE CHAIR: Rachel Segalman

• Polymer Upcycling Megan Robertson, Karen Winey, Gregg Beckham, Linda Broadbelt

• Solid Polymer Electrolytes Nitash Balsara, Jodie Lutkenhaus, Monika Schoenhoff, Jennifer Schaefer, Emmanouil Glynos, Moon Jeong Park

• Limits of Macromolecular Self-Assembly Arthi Jayaraman, Lynn Walker, Mahesh Mahanthappa, Oleg Gang

• Nanocomposites Russell Composto, Jane Lipson, Michael Rubinstein, So Youn Kim, Reika Katsumata, Marc Couty

• Novel Characterization Methods Christopher Soles, Danielle Mai, Enrique Gomez, Brian Collins, Muzhou Wang

• Artificial Intelligence and Machine Learning Jonathan Whitmer, Alexander Hexemer, Debra Audus, Venkat Ganesan

• Dynamic Networks Bradley Olsen, Vivek Sharma, Evelyne van Ruymbeke, Jian Qin

• Membranes Chinedum Osuji, Richard Register, Benny Freeman, Sangwoo Lee, Miguel Modestino, Ayse Asatekin

• Biomaterials Thomas Epps, Matthew Tirrell, LaShanda Korley,

Emerging Roles of RNA in Gene Regulation JUL 9-10, 2022 CHAIRS: Nicole Martinez and Ana Fiszbein

Jayaraman

Polymer Physics Leveraging Polymer Physics for a More Sustainable Future

Post-Transcriptional Gene Regulation Coordination and Integration of RNA Processing from Transcription to Translation JUL 10-15, 2022 JORDAN HOTEL AT SUNDAY RIVER, NEWRY, ME CHAIRS: Tom Cooper and Kristen Lynch VICE CHAIRS: Karla Neugebauer and Nicholas Conrad

• Emerging Concepts in RNA Biology Joan Steitz, Christine Mayr, Mitch Guttman, Benjamin Blencowe, Roy Parker

• Role of Post-Transcriptional Regulation From Genotype to

Phenotype Brenton Graveley, Xinshu Xiao, Juan Valcarcel, Alain Laederach, Angela Brooks, Auinash Kalsotra, William Fairbrother

• 3’ End Processing Chris Burge, Eric Wagner, Bin Tian, Yongsheng Shi • RNA Decay Karla Neugebauer, Lynne Maquat, Olivia Rissland, Bobby Hogg, Heidi Cook-Andersen, Sujatha Jagannathan

• RNA Structure and Modifications Wendy Gilbert, Steve Bonilla, Richard Gregory, Kathy Fange Liu, Rui Zhao

• Regulation of Translation Ruth Lehmann, Katrin Karbstein, Davide Ruggero, Gloria Brar, Joel Neilson, Jeff Coller

Health and Disease Brooke Farrugia, Vincent Hascall, Sylvie Ricard-Blum, Jamie Thompson, Adam Hall

• Development of New Drugs Targeting

Proteoglycans Jin-Ping Li, Ralph Sanderson, Jeremy Turnbull, • Matrix-Targeted Glycan Therapeutics in Clinical

Trials Glenn Prestwich, John Paderi, Li Peng, Sangeetha Srinivasan, Mats Wahlgren, Denis Barritault, Thomas Kennedy, Abigail Pulsipher

• The GRC Power Hour™ Catherine Merry

Proteoglycans

From Cell Biology to Human Disease

JUL 9-10, 2022

JUL 17-22, 2022 COLBY-SAWYER COLLEGE, NEW LONDON, NH CHAIR: Alan Attie VICE CHAIR: Julia von Blume

CHAIRS: Marissa Maciej-Hulme and Ryan Weiss

• Protein Folding in the Secretory Pathway Regina Fluhrer, Jason Gestwicki, Carmine Settembre, Feroz Papa, Feyza Engin

• Glycosylation and Phosphorylation in the Secretory Pathway Melkam Kebede, Hudson Freeze, Heather Flanagan-Steet, Kelly Ten Hagen, Michael Boyce

• Nutrient Sensing, Ion Channels and Vesicle Trafficking Peter Arvan, Matthew Merrins, Debbie Thurmond, Samuel Stephens, Melkam Kebede

• Protein Aggregation, Proteostasis and Autophagy Feyza Engin, Mondira Kundu, Luigi Puglielli, Judith Frydman

• COVID-19 Entry Into the Cell and Assembly in the

Secretory Pathway Carmine Settembre, Gary Whittaker, Nihal Altan-Bonnet, Hector Aguilar-Carreno

• Visualizing the Secretory Pathway Julia von Blume, Ana Paula Arruda, Anjon Audhya, Michele Solimena, Joerg Bewersdorf

• Lipid Transport Through the Secretory Pathway Michele Solimena, Anant Menon, Russell Debose-Boyd, Thomas Melia, Elina Ikonen

• Proteolysis in the Secretory Pathway Nabil Seidah, Thomas Delong, Annik Prat, Regina Fluhrer, Stefan Lichtenthaler

• Exosomes Anjon Audhya, Carmella Evans-Molina, Philipp Scherer, Wei Guo

• The GRC Power Hour™ Julia von Blume, Iris Lindberg

Protein Processing, Trafficking and Secretion Insights into the Molecular Mechanisms of Protein Trafficking JUL 16-17, 2022 CHAIRS: James Checco and Julie Cruanes

JUL 23-24, 2022 CHAIRS: Whitney Loo and Konane Bay

• New Technologies to Define the Role of PGs and GAGs in

Protein Processing, Trafficking and Secretion

Sarah Heilshorn

• The GRC Power Hour™ Lilo Pozzo, Rodney Priestley, Arthi

Forsberg-Nilsson, Stephen Hewitt, Fotis Asimakopoulos, Mattias Belting, Wantong Yao, Paul Timpson

Nunzio Bottini, Jian Liu, Mitchell Ho

Post-Transcriptional Gene Regulation

• Keynote Session: Technology Translation Albert Polman,

• Proteoglycans and GAGs in Immuno-Oncology Karin

Integrated Proteoglycan Research to Improve Human Health

Proteolytic Enzymes and Their Inhibitors The Regulation of Proteolysis in Health, Disease and Treatment JUN 5-10, 2022 RENAISSANCE TUSCANY IL CIOCCO, LUCCA (BARGA), ITALY CHAIR: James Huntington VICE CHAIR: Jeanne Hardy

• Cancer Klaudia Brix, Galia Blum, Donna Small, Boris Turk • Coagulation Proteases Rodney Camire, Jim Crawley, Joanna Koziel, Christoph Reinhardt, Thomas Renné

• Immunity and Inflammation James Whisstock, Charaf Benarafa, F. Xavier Gomis-Rüth, Piet Gros, Guy Salvesen

• Proteases and Pathogens Jan Potempa, Charles Craik, Ruby Law, Celia Schiffer

• Therapeutic Targeting of Proteolytic Activity Joanne Lemieux, Grant Blouse, Henry Maun, Dennis Wolan

• The Ubiquitin-Proteosome System Paula Da Fonseca, Andreas Martin

• Probing Protease Action In Situ Marcin Drag, Matthew Bogyo, Laura Edgington-Mitchell, Paulina Kasperkiewicz

• Proteolysis in and on Cell Membranes Manu Platt, Christoph Becker-Pauly, Regina Fluhrer, Rui Zhou

• SARS-CoV-2 Proteases and Inhibitors Jeanne Hardy, Rolf Hilgenfeld, Christopher Overall, Joanne Lemieux

• The GRC Power Hour™ Galia Blum

Proteolytic Enzymes and Their Inhibitors The Regulation of Proteolysis in Health, Disease and Treatment JUN 4-5, 2022

Proteoglycans Frontiers in Basic and Translational Proteoglycan Research to Improve Human Health JUL 10-15, 2022 PROCTOR ACADEMY, ANDOVER, NH CHAIRS: Liliana Schaefer and Charles Frevert VICE CHAIR: Catherine Merry

• Keynote Session: Recent Progress in Proteoglycan Biology Marian Young, Renato Iozzo, Peter Seeberger

• Genetic Defects Linking Proteoglycans and

Glycosaminoglycans to Clinical Phenotypes and Tissue Pathologies Thomas Wight, Suneel Apte, Fransiska Malfait, Josephina Meester, Eri Arikawa-Hirasawa, Mark Febbraio

• Proteoglycans and Associated Molecules in Tissue

Homeostasis and Disease Billy Hudson, Nikos Karamanos, Nicola Allen, Joseph Hippensteel, Anthony Day • Proteoglycan Signaling Melanie Simpson, Jeffrey Esko, Mythreye Karthikeyan, Jorge Filmus, Aaron Petrey, Rashmin Savani

• Proteoglycans in Development and Regenerative Medicine Hideto Watanabe, John Whitelock, Alyssa Panitch, Tommaso Pizzorusso

CHAIRS: Paulina Kasperkiewicz and Amy Weeks

Quantum Science Many-Body Quantum Systems: From Quantum Computing and Simulation to Metrology and Coherent Light-Matter Hybrids JUL 24-29, 2022 STONEHILL COLLEGE, EASTON, MA CHAIRS: Markus Greiner and Eugene Demler VICE CHAIRS: Susanne Yelin and Jonathan Simon

• Quantum Simulation Ana Maria Rey, Monika Aidelsburger, Fabian Grusdt

• Progress in Quantum Computing and Algorithms Mikhail Lukin, Andrew Houck, Matthias Troyer

• Non-Equilibrium Quantum Matter Monika Aidelsburger, Richard Averitt, Waseem Bakr, Ana Maria Rey, Julian Léonard

• From Quantum Simulation to Quantum Computing Eun-Ah Kim, Rainer Blatt, Dries Sels, Mikhail Lukin

• Quantum Metrology and Sensing Susanne Yelin, Ania Bleszynski-Jayich, Holger Mueller, Vladan Vuletic

• Late-Breaking Topics Andrew Houck

• Quantum Matter Andrea Cavalleri, Amir Yacoby, Andrea Young, Sankar Das Sarma

• Light-Matter Interactions and Many-Body Quantum Optics Jonathan Simon, Andrea Cavalleri, Angel Rubio, Ephraim Shahmoon

• Connection Between Quantum Science and Other

Fields Vladan Vuletic, Eun-Ah Kim

Quantum Science Quantum Matter for Communications, Fundamental Investigations, Simulation and Computation JUL 23-24, 2022 CHAIRS: Julia Cline and Kristine Rezai

Radionuclide Theranostics NEW! for the Management of Cancer Molecularly Targeted, Radioactive Cancer Diagnosis and Therapy JUL 17-22, 2022 JORDAN HOTEL AT SUNDAY RIVER, NEWRY, ME CHAIR: Alan Harris VICE CHAIR: Yusuf Menda

• Targets and Radionuclides Michael Schultz, David Bauer, Germo Gericke

• Radiotherapeutics in Oncologic Diseases Daniel Pryma, Ken Herrmann, Ebrihim Delpassand, Amir Iravani, Michael Schultz

• Dosimetry-Guided Therapy with Radionuclides Stephen Graves, Robert Hobbs

• Development of Theranostic Radiopharmaceuticals Jonathan McConathy, Richard Wahl, Andrew Bellizzi, Benjamin Larimer

• Radionuclide Therapy in Clinical Practice Joseph Dillon, John Buatti, Eric Liu, Daniel Pryma, Stephen Graves

Research at High Pressure

Salt and Water Stress in Plants

Exploring High Pressure Science at the Extremes Through Experiment and Computation

Mechanisms of Abiotic Stress Resilience and Applications for Agriculture

JUL 17-22, 2022 HOLDERNESS SCHOOL, HOLDERNESS, NH CHAIR: Sakura Pascarelli VICE CHAIR: Chris Pickard

MAY 22-27, 2022 LES DIABLERETS CONFERENCE CENTER, LES DIABLERETS, SWITZERLAND CHAIRS: Jose Dinneny and Christa Testerink VICE CHAIRS: Thomas Juenger and Amelia Henry

• Challenges to Our Understanding of Dense Matter Russell Hemley, Paul Loubeyre

• Hydrogen Rich Systems Yanming Ma, Mikhail Eremets, Audrey Grockowiak, Ashkan Salamat, Dmitrii Semenok

• Beyond Earth: Pressure as an Experimental Probe Amy Jenei, Stephanie Brygoo, Sara Seager

• Scientific Opportunities Opened by New Experimental

Approaches Siegfried Glenzer, Stewart McWilliams, Thomas Meier, Mohamed Mezouar

• Earth: From Crust to Inner Core Renata Wentzcovitch, Yanhao Lin, Taku Tsuchiya

• The Limits of Computation and the Role of Data Driven

Approaches Maosheng Miao, Kien Nguyen-Cong, Volker Deringer, Clemens Prescher, Eva Zurek

• Extreme Bioscience Ryo Kitahara, Catherine Royer, Karen Lloyd • New Phenomena at High Density Guoyin Shen, Graeme Ackland, Leonid Dubrovinsky

• Keynote Session: Extremely Dense Matter Chris Pickard, Jon Eggert, Andrea Kritcher, Burkhard Militzer

• Design of Theranostic Clinical Trials David Bushnell, Philip Harris, Charles Kunos, Emily Bergsland

• Advances in Radionuclide Theranostics John Buatti, Aldo Scarpa, Brian Miller, Chandrasekhar Bal

• Selected Poster Presentations Yusuf Menda • The GRC Power Hour™

Renewable Energy: Solar Fuels

Synergy Between Experiment and Computation Within Science at the Extremes

Combining Laboratory Measurements with Observational Constraints to Understand Tectonic Processes AUG 7-12, 2022 BATES COLLEGE, LEWISTON, ME CHAIR: Daniel Faulkner VICE CHAIR: Heather Savage

• Keynote Session: Lithospheric Rheology from Small-Scale

Experiments David Kohlstedt, Brian Evans, Philip England

• Early-Career Investigator Presentations Heather Savage

• Light Absorbers and Photocatalysts Marcella Bonchio, Kyoung-Shin Choi, Osamu Ishitani, Li-Zhu Wu

• Water Splitting Licheng Sun, Bin Liu, Peter Strasser • Operando Spectroscopy Moniek Tromp, Hao Ming Chen, Beatriz Roldan Cuenya

• CO2 Reduction Alexander Miller, Karen Chan, Matthew Kanan, Marc Robert

• Systems and Engineering Harry Atwater, Curtis Berlinguette, Hans Geerlings, Avner Rothschild, Wilson Smith

• Late-Breaking Topics Can Li

Renewable Energy: Solar Fuels Catalytic Transformations for Sustainable Chemicals MAY 7-8, 2022 CHAIRS: Anna Beiler and Shannon Bonke

Julkowska, Maheshi Dassanayake, Melvin Oliver

• Rhizosphere Interfaces with Soil, Water and Ions Daniela Dietrich, Andrea Carminati, Malcolm Bennett, Siobhan Brady, Niko Geldner

• Interfaces with Soil and Microbes Sheng Yang He, Jennifer Pett-Ridge, Cyril Zipfel, Rumyana Karlova

• Omic Approaches to Understanding Stress Acclimation Robert VanBuren, Sonia Negrao, David Des Marais, Malia Gehan, Jill Farrant Guillaume Lobet, Matthew Gilliham, Noel Holbrook

• The GRC Power Hour™ Thomas Juenger, Julia Bailey-Serres

MAY 21-22, 2022

Rock Deformation

• Solar Fuels at Sunrise Jillian Dempsey, Raffaella Buonsanti, Haotian

Amanda Morris, Yogesh Surendranath

• Adaptation to Water Stress and Salinity Magdalena

Unraveling Plant Stress Responses Using Multidisciplinary Approaches

• Earthquake Mechanics Roland Burgmann, Nadia Lapusta,

• Merging Molecules with Materials Greta Patzke, Bettina Lotsch,

Henry, Marjorie Lundgren, Moises Exposito-Alonso, Diana Santelia, Andrew Leakey

Salt and Water Stress in Plants

MAY 8-13, 2022 RENAISSANCE TUSCANY IL CIOCCO, LUCCA (BARGA), ITALY CHAIRS: Clifford Kubiak and Xile Hu VICE CHAIRS: Can Li and Jillian Dempsey

Erb, Jenny Yang

Dehesh, Takashi Hashimoto, Staffan Persson, Jürgen Kleine-Vehn

• Photosynthesis, Climate Change and Agriculture Amelia

JUL 16-17, 2022

• Fundamental Frictional Processes Marco Maria Scuderi,

• Biological and Bio-Inspired Systems Marc Fontecave, Tobias

Zhen-Ming Pei, Rashmi Sasidharan, Liwen Jiang, Sean Cutler

• Cellular Organization and Stress Response Katayoon

CHAIR: Dean Smith

Advancing Complexity, Selectivity and Efficiency in Artificial Photosynthesis

Wang

Resilience Julia Bailey-Serres, Katayoon Dehesh, David Salt • Signaling Mechanisms and Stress Response Claudia Jonak,

• Tissue Hydraulics and Plant Physiology Yann Boursiac,

Research at High Pressure

• Optimizing Therapy Kjell Oberg, Jonathan McConathy, David Bushnell, Josh Mailman

• Keynote Session: Mechanisms of Stress Signaling and

Izabela Szlufarska, David Goldsby, Kathryn Hayward Gregory McLaskey

• Fault Slip in Nature Zoe Mildon, Rachel Abercrombie, Matt Tarling, Marion Thomas

• Lower Crustal Dynamics Virginia Toy, William Shinevar, Luca Menegon, Ylona Dinther

• Mantle Rheology Benjamin Holtzman, Sylvie Demouchy, David Dobson • Shallow Subduction Processes Christine Regalla, Noel Bartlow, Rob Skarbek, Demian Saffer

• Deeper Subduction Processes Nadege Hilairet, Geoff Abers, Greg Hirth

• The GRC Power Hour™

CHAIRS: Stephanie Klein and Abdeljalil Elhabti

Scientific Methods in Cultural Heritage Research Integrating Multidisciplinary Approaches for Deeper Characterization, Interpretation and Preservation of Heritage JUL 10-15, 2022 LES DIABLERETS CONFERENCE CENTER, LES DIABLERETS, SWITZERLAND CHAIRS: Julie Arslanoglu and Loïc Bertrand VICE CHAIRS: Admir Masic and Costanza Miliani

• Keynote Session: Insights and Visions Connecting Cultural

Heritage Research Katrien Keune, Hartwig Fischer, Caroline Tokarski • Artistic and Conservation Practice-Driven Material Study Marika Spring, Daryl Howard, Maartje Stols-Witlox, Ilaria Bonaduce

• Computational Advances Driving New

Interpretations Agnès Desolneux, Michalina Pacholska, Livio de Luca • Study of Ancient and Historical Biological Materials Clara Granzotto, Elizabeth Henaff, Theanne Schiros

• Heritage Material Systems from Nanometric to Macroscopic

Scales Dominique Derome, Lara Maldanis, Letizia Monico, Patrick Dietemann

• Safer Experimental Conditions for Heritage Studies Costanza Miliani, Nathan Wales, Samuel Webb, G. Asher Newsome

• Engineering and Materials Sciences in Cultural Heritage

Rock Deformation Integrating Rock Deformation Studies with Geophysics, Field Geology and Modeling AUG 6-7, 2022 CHAIRS: Taka Kanaya and Carolyn Tewksbury-Christle

Research Johanna Leissner, Lukasz Bratasz, Daniel Asmar, Laurence De Viguerie

• Novel Materials Inspired by Ancient Materials and

Practices Clément Sanchez, Marie Jackson, Roberto Giustetto, Romain Bordes

• Keynote Session: Future Frontiers for Heritage Research

by Strengthening Collaboration Between the Humanities and Science Barbara Berrie, Francesca Casadio, Yannick Rochat, Johanna Tummers

• The GRC Power Hour™ Teresa Duncan, Alicia McGeachy

Scientific Methods in Cultural Heritage Research Innovation in Materials and Technologies for the Analysis and Conservation of Heritage JUL 9-10, 2022

Single-Cell Genomics

Signaling by Adhesion Receptors Examining the Basic Biomechanics and Biomedical Aspects of Cell Adhesion Signaling

MAY 1-6, 2022 LES DIABLERETS CONFERENCE CENTER, LES DIABLERETS, SWITZERLAND CHAIRS: Xiaoliang Sunney Xie and Stephen Quake VICE CHAIRS: Xiaowei Zhuang and Barbara Treutlein

JUL 16-17, 2022 CHAIRS: Kate Cavanaugh and Fiona Passanha

CHAIRS: Victor Gonzalez and Teresa Duncan

Signal Transduction by Engineered Extracellular Matrices Microenvironmental Regulation of Stem and Somatic Cells in Organismal Development and Regenerative Medicine JUL 24-29, 2022 SOUTHERN NEW HAMPSHIRE UNIVERSITY, MANCHESTER, NH CHAIRS: David Schaffer and Matthias Lutolf VICE CHAIRS: Shelly Peyton and Sanjay Kumar

• Keynote Session: Exploring and Manipulating the

Cell-Matrix Interface in Health and Disease Adam Engler, Valerie Weaver, Juergen Knoblich

• Organoids Alex Hughes, Jianping Fu, Nuria Montserrat • Organs-on-a-Chip Peter Loskill, Nancy Allbritton, Roger Kamm • Advanced Engineered ECMs Shyni Varghese, Sarah Heilshorn, Cole DeForest, Jason Burdick

• Single Cell Biology and Development Karthik Shekhar, Siddharth Dey, Tom Nowakowski

• ECM Mechanobiology Catherine Kuo, Xavier Trepat, Ovijit Chaudhuri, Celeste Nelson

• ECM and Stem Cell Fate Regulation Kris Kilian, Samira Musah, Randy Ashton

• Bioinspired Fabrication Fabien Guillemot, Jordan Miller, Kelly Stevens, Akhilesh Gaharwar

• Engineering and Application of Immune-Modulatory Materials

Single Molecule Approaches to Biology

• Single-Cell Transcriptomics Dana Pe'er, Long Cai, Rickard Sandberg, Jianbin Wang

Uncovering Physical Principles of Life with Single Molecule Approaches

• Imaging Robert Singer, Hazen Babcock, Alistair Boettiger, Arjun Raj,

JUL 3-8, 2022 REY DON JAIME GRAND HOTEL, CASTELLDEFELS, SPAIN CHAIRS: Erwin Peterman and Olga Dudko VICE CHAIRS: Samuel Hess and Suliana Manley

• Genomes Ido Amit, Paul Blainey, Dong Xing, Chenghang Zong

Loic Royer

• Keynote Session: Probing the Non-Equilibrium Nature of Life Carlos Bustamante, John Marko, Rob Phillips

• Diffusion as Transport Mechanism in the Cell Samuel Hess, Julie Biteen, Maria Garcia-Parajo, David Holcman, Cornelis Murre

Signal Transduction by Engineered Extracellular Matrices Nano to Macroscale Engineering in Biology and Regenerative Medicine JUL 23-24, 2022 CHAIRS: Claudia Loebel and Woojin Han

Signaling by Adhesion Receptors Adhesion Across Scales: From Molecules to Morphogenesis JUL 17-22, 2022 SOUTHERN NEW HAMPSHIRE UNIVERSITY, MANCHESTER, NH CHAIR: Ann Miller VICE CHAIR: Patrick Derksen

• Keynote Session: Adhesion Across Scales: From Molecules

to Morphogenesis Patrick Derksen, Bob Goldstein, Kathleen Green • Mechanotransduction by Adhesion Receptors Christopher Chen, Carl-Philipp Heisenberg, Erin Cram, Patrick Oakes

• Maintaining Adhesion in Dynamic Environments Adam Martin, Carien Niessen, Yusuke Toyama, Jennifer Zallen

• Adhesive Control of Cell Division Cara Gottardi, Yohanns Bellaïche, Sarah Woolner, Martijn Gloerich

• Advances in Adhesion Signaling Alpha Yap, Rafael Garcia-Mata, Tony Koleske, Alexa Mattheyses

• Adhesion Signaling and Cell Migration Tony Koleske, Danijela Matic Vignjevic, Maddy Parsons, Sally Horne-Badovinac

• Engineering Adhesion Martin Schwartz, Christopher Chen, Sanjay Kumar, Karen Kasza

• Adhesion, Morphogenesis and Tissue Remodeling Bob Goldstein, Scott Holley, Adam Martin, Robert Krauss

• Adhesion and Disease Kathleen Green, Asma Nusrat • The GRC Power Hour™

• Epigenetics Alexander Meissner, Yunlong Cao, Wolf Reik, Fuchou Tang, Jan Vijg

• 3D Genome Structures and Dynamics Amos Tanay, Peter Fraser, William Greenleaf, Kikue Tachibana

• Innovations in Genomic Technologies Piero Carninci, Martin Enge, Emma Lundberg, Nikolai Slavov, Jonathan Weissman

• Applications to Cancer and Immunology Michael Clarke,

• Beating the Diffusion Speed Limit: Biological

Motors Stefan Diez, Carlos Bustamante, Cees Dekker, Lukas Kapitein • Navigating Energy and Fitness Landscapes Hermann Gaub, Irene Chen, Thomas Perkins, Michael Woodside

Charles Gawad, Nicholas Navin, Zemin Zhang

• Applications to Neurobiology Hongkui Zeng, Michelle Chen, Joseph Ecker, Ge Gao, Bosiljka Tasic

• Human and Model Organism Cell Atlas Michael Levine,

• The Dynamic Nature of Cellular Structures Zan Luthey-Schulten, Ariel Amir, Patricia Bassereau, Daniel Needleman

• Crossing the Phase Boundary Patricia Bassereau, Ibrahim Cisse,

Spyros Darmanis, Camille Ezran, Aki Minoda

• The GRC Power Hour™

Yaojun Zhang, Gary Karpen

• Biology in Bits: Information Approaches Suliana Manley, Naama Brenner, Yoav Shechtman, Gasper Tkacik

• Searching for Principles in Biological Complexity Marileen Dogterom, Toshio Ando, Taekjip Ha, Zan Luthey-Schulten, Antoine Van Oijen

• Keynote Session: From Single Molecules to Unifying

Principles of Life Taekjip Ha, Petra Schwille, Stefan Grill • The GRC Power Hour™

David Wilson, Takahsi Kishimoto, Ankur Singh

• The GRC Power Hour™ Sarah Heilshorn

NEW!

When Stochasticity Meets Precision in a Single Cell

Solid State Chemistry Functional Inorganic Materials: Exploratory Synthesis, Advanced Characterization and Computational Methods JUL 24-29, 2022 COLBY-SAWYER COLLEGE, NEW LONDON, NH Chair: Shiv Halasyamani Vice Chair: Arthur Mar

• Quantum and Layered Materials Arthur Mar, Leslie Schoop,

Single Molecule Approaches to Biology

Andrew Grosvenor

Single Molecule Perspectives for a Deeper Understanding of Biology

• Energy Materials Linda Nazar, Jakoah Brgoch, Taylor Sparks, Serena

JUL 2-3, 2022 CHAIRS: Lukas Milles and Carleen Kluger

• Advanced Characterization Methods Katherine Page, John

Single-Cell Cancer Biology

Cussen, John Vaughey Evans, Joke Hadermann

NEW!

Dissecting Evolution and Heterogeneity of Single Cancer Cells

• Synthesis of Functional Materials Simon Clarke, Michael Hayward, Daniel Shoemaker, Mario Bieringer, Bayram Saparov

• Computational Methods James Rondinelli, Nicole Benedek, Elsa A. Olivetti

JUN 12-17, 2022 STONEHILL COLLEGE, EASTON, MA CHAIRS: Kai Tan and Nicholas Navin VICE CHAIRS: Mario Suva and Sohrab Shah

• Non-Oxide Materials Julia Chan, Paul Canfield, Kanishka Biswas,

• Pre-Malignancies and Early-Stage Tumors Samuel Aparicio,

• Non-Oxide Materials: Superconductors, Hydrides and

Kai Kessenbrock, Xin Lu, Jorge Reis-Filho

• Solid Tumors Devon Lawson, Samuel Aparicio, Sam Behjati, Michalina Janiszewska, Peter Van Loo

• Hematological Tumors Iannis Aifantis, Charles Gawad, Catherine

Oliver Janka, Stefanie Dehnen

• Chemistry in Industry Kenneth Poeppelmeier, William Sheets, Erin Sorenson

Magnetocalorics Danna Freedman, Weiwei Xie, Ulrich Häussermann, Bettina Lotsch, Yurij Mozharivskyj • Modulated Structures Daniel Fredrickson, Sven Lidin • The GRC Power Hour™ Danna Freedman, Nicole Benedek

Wu, Koichi Takahashi, Adam Mead

• Epigenomic Heterogeneity Catherine Wu, Nicola Aceto, Andrew Adey, Ansuman Satpathy, Celine Vallot

• Tumor-Immune Cell Interactions in Tumor Microenvironment Mario Suva, Iannis Aifantis, Itay Tirosh, Zemin Zhang

• Computational Methods for Single-Cell Analysis Sohrab Shah, Ken Chen, Dana Pe'er, Rahul Satija, Nancy Zhang

Solid State Chemistry Functional Inorganic Materials: Exploratory Synthesis, Advanced Characterization and Computational Methods JUL 23-24, 2022 CHAIRS: Rebecca Smaha and Yuzki Oey

• Current Advances in Single-Cell Technologies Klaus Pantel, Bernd Bodenmiller, Dario Bressan, Joakim Lundeberg

• Circulating Tumor Cells and Metastasis Xin Lu, Daniel Haber, James Hicks, Klaus Pantel

• Therapeutic Resistance Michalina Janiszewska, Maxim Artyomov, Liynat Jerby-Arnon, Devon Lawson, Kornelia Polyak

• The GRC Power Hour™

Solid State Studies in Ceramics Coupled Phenomena in Ceramics Across Length Scales AUG 7-12, 2022 MOUNT HOLYOKE COLLEGE, SOUTH HADLEY, MA CHAIR: Ivar Reimanis VICE CHAIRS: Wayne Kaplan and Edwin Garcia

• Achieving Exceptional Responses in Structural Materials Brian Cox, Julia Greer, Kevin Hemker

• Thermo-Mechanical Behavior in Extreme

Environments William Fahrenholtz, Alexandra Navrotsky, David Poerschke, Frank Zok

• Processing Complex Structures Lisa Rueschhoff, Rajendra Bordia, Jennifer Rupp

• Interfaces and Grain Boundaries Fadi Abdeljawad, Yuichi Ikuhara, Amanda Krause, David Srolovitz

• Evolving Therapeutic Approaches and Methodologies Adam Ratner, Annaliesa Anderson, Joshua Osowicki

• Early-Career Investigator Presentations Michael Federle • The GRC Power Hour™ Elaine Tuomanen

• Defects in Ceramics Nasim Alem, William Bowman, Elizabeth Dickey

• Interfaces and Electrical Charge Sossina Haile, Wolfgang Rheinheimer, Klaus van Benthem, Roger De Souza

• Coupled Phenomena in Oxides Kelsey Hatzell, Nicola Perry, Bilge Yildiz

Streptococcal Biology Physiology, Host-Interactions and Vaccine Development and Epidemiology of Streptococci CHAIRS: Brady Spencer and Lamar Thomas

• The GRC Power Hour™

Solid State Studies in Ceramics Fundamental Phenomena in Ceramics from the Atomistic Level to the Microstructure AUG 6-7, 2022 CHAIRS: Hadas Sternlicht and Jasmin Koldehoff

Structural Nanomaterials

Different Forms of Stereochemistry: From Catalysis and Synthesis to Macromolecules and the Natural World JUL 24-29, 2022 SALVE REGINA UNIVERSITY, NEWPORT, RI CHAIRS: Varinder Aggarwal and Eric Ashley VICE CHAIRS: Eric Jacobsen and Tamas Benkovics

• Keynote Session: Synthesis and Translation to Medicine Eric Jacobsen, Sarah Reisman, Paul Wender

• Stereochemistry of Radicals and Peptides Alastair Lennox, Michelle Chang, Ivan Huc, Song Lin, Alison Wendlandt

• Functionalization of Multiple Bonds Santanu Mukherjee, Keary Engle, Tomislav Rovis, Ryan Shenvi Gregory Fu, Matthew Gaunt, Kyle Mack, Franziska Schoenebeck Doyle, Bill Morandi, Corinna Schindler

• Discovery and Synthesis of Medicinal Molecules Juana Du, Cameron Cowden, Andrew Neel, Robert Singer, Linli Wei

• Catalysis and Sustainability Tian Qin, Josep Cornella, Daniele Leonori, Alison Narayan

• Asymmetric Catalysis and Mechanism Nicholas Race, Guy Lloyd-Jones, Keiji Maruoka, James Morken

• Keynote Session: De Novo Generation of Chirality Tamas Benkovics, Michael Mcbride, Richmond Sarpong

• The GRC Power Hour™ Eric Ashley, Sarah Reisman

• Keynote Session: Materials Design at the Nanoscale

• Aging as a Systemic Process Ned David, Meng Wang, Danica

Ruth Schwaiger, Christopher Schuh, Diana Farkas

Microstructures Lei Lu, Wendy Gu, Thomas Waitz, Koichi Tsuchiya • Advanced Characterization Techniques Aslan Ahadi, Erica Lilleodden, Jason Trelewicz

• Mechanics at the Nanoscale Chelsea Appleget, Daniel Kiener,

Horst Hahn, C. Cem Tasan

• Advances in Hierarchical Materials Design Mingxin Huang, Lorenzo Valdevit, Christoph Eberl, Yang Lu

• Atomistic and Nanoscale Simulations Paulo Branicio, Mark Asta, David Srolovitz

• Heretical Material Design and Properties Timothy Rupert, Alfonso Ngan, Ralph Spolenak, Qiming Wang

• Non-Equilibrium Structures Xun-Li Wang, Gerhard Dehm, Yilong Han

Synaptic Transmission Fine-Scale Synaptic Interactions in Space and Time JUN 19-24, 2022 RENAISSANCE TUSCANY IL CIOCCO, LUCCA (BARGA), ITALY CHAIR: Alison Barth VICE CHAIRS: Daniel Choquet and Graeme Davis

• Regulation and Virulence Mechanisms Elaine Tuomanen,

Jing-Dong Han, Alex Zhavoronkov, Kristen Fortney, Albert-Laszlo Barabasi Chen, Jessica Tyler

• Comparative Genomics of Aging Andrei Seluanov, Vera Gorbunova, Emma Teeling, João Pedro de Magalhães

• Fundamental Bases of Aging Cynthia Kenyon, Kenneth Raj, Daniel Promislow

• The GRC Power Hour™ Morgan Levine

Systems Chemistry Life-Like and Emergent Behavior in Complex Molecules and Ensembles JUN 26-JUL 1, 2022 JORDAN HOTEL AT SUNDAY RIVER, NEWRY, ME CHAIRS: Sijbren Otto and Rein Ulijn VICE CHAIRS: Rebecca Schulman and Rafal Klajn

• From Self-Assembly to Life Through Modelling and Experiment Rebecca Schulman, David A. Leigh, Ramanarayanan Krishnamurthy David Lynn, Gonen Ashkenasy, Eörs Szathmáry, Oliver Trapp, Kerstin Göpfrich

• Fueled Reaction Networks and Metabolic Materials Sergey Semenov, Kenneth Showalter, Agota Toth, Massimo Baroncini

• Navigating Shallow Energy Landscapes in Supramolecular

Systems Julia Ortony, Allie Obermeyer, Matthew Rosseinsky, Tell Tuttle, Jonathan Nitschke, Sarah Perry, Akif Tezcan

• Emergent Catalysis, Machines and Motility Ivan Korendovych,

• Synapses and Social Behavior Helene Marie, Robert Malenka

Beatriu Escuder, Steve Granick, Daniela Wilson, Nathalie Katsonis

• Presynaptic Regulation Noa Lipstein Lipstein, Gwyneth Card,

• Active and Adaptive Materials Through Molecular

Annette Dolphin, Timothy Ryan, Matthijs Verhage

• Imaging Synaptic Structure Thomas Blanpied, Kristen Harris, Michael Higley, Na Ji, Valentin Nägerl James Poulet, Marlene Bartos, Lucy Palmer

• Multisynaptic Interactions Pablo Castillo, Kevin Bender, Yishi Jin,

Camilli, Mark Davies, Bill Hanage

Ward-Caviness, Morten Scheibye-Knudsen, Brian Kennedy, Paola Sebastiani

• Artificial Intelligence and Machine Learning Marc Kirschner,

• Origins and Synthesis of Life Ramanarayanan Krishnamurthy,

Evolving Genomes, Behavior and Pathogenic Mechanisms of Streptococci and Enterococci

Jan-Willem Veening, Michael Gilmore, Victor Nizet

Daniel Belsky, Sara Hagg

Megan Cordill, Corinne Packard

• Synthesis of New Nanostructures and Alloys Blythe Clark,

• Synaptic Function in Disease Bruce Herring, Paola Arlotta, Gaia

• Evolution of Genomes: From Genomics to Function Andrew

Martin Borch Jensen, Joris Deelen

• Clinical and Molecular Biomarkers Meng Wang, Cavin

Streptococcal Biology

• Keynote Session: Insights into Pathogen and Host Biology

• Genomics of Aging Emma Teeling, Nicholas Schork, Ed Boyden,

MAY 8-13, 2022 LES DIABLERETS CONFERENCE CENTER, LES DIABLERETS, SWITZERLAND CHAIRS: Qing Ping Sun and Andrea Hodge VICE CHAIRS: Lei Lu and Xun-Li Wang

• In Vivo Synaptic Transmission Mario Penzo, Johannes Letzkus,

AUG 14-19, 2022 JORDAN HOTEL AT SUNDAY RIVER, NEWRY, ME CHAIRS: Kelly Doran and Shiranee Sriskandan VICE CHAIRS: Michael Federle and Jan-Willem Veening

• Epigenetic Reprogramming and Rejuvenation Felipe Sierra,

• Epigenetic Biomarkers Kristen Fortney, Riccardo Marioni, Ake Lu,

• Transition Metals in Asymmetric Catalysis Robert Paton, • Functionalization of Strong Bonds Shauna Paradine, Abby

• Delaying and Reversing Aging Steve Horvath, Cynthia Kenyon,

Design, Microstructure and Mechanical Behavior of Structural Nanomaterials

• Homogeneous and Heterogeneous Nanoscale

Stereochemistry

MAY 29-JUN 3, 2022 GRAND SUMMIT HOTEL AT SUNDAY RIVER, NEWRY, ME CHAIR: Vadim Gladyshev VICE CHAIR: Steve Horvath

Manuel Serrano, Vittorio Sebastiano, Jacob Kimmel, Morgan Levine

Marina Filip, Annamaria Petrozza Kisailus

NEW!

Systemic Processes, Omics Approaches and Biomarkers in Aging

Richard Miller

AUG 13-14, 2022

• Perovskites for Optoelectronics Bryan Huey, David Cahen, • Biological Materials in the Extreme Olivia Graeve, David

Systems Aging

Novarino, Morgan Sheng Thomas Nevian, Inna Slutsky

• Synaptic Computation and Network Design Srikanth

Self-Assembly Rienk Eelkema, Job Boekhoven, Andreas Walther, Adam Braunschweig, Ronit Freeman

• Active and Adaptive Materials Based on Nanoparticles or

Colloids Rafal Klajn, Anna Balazs, Robert Macfarlane, Willem Noorduin, Alfredo Alexander-Katz

• Biological Systems Chemistry Ayala Lampel, Wilhelm Huck, Henry Hess, Cecilia Leal, Ilja Voets, Roy Bar-Ziv

• Systems Chemistry in Flow Peter Korevaar, Lee Cronin, Andrew Griffiths, Steven Benner

• The GRC Power Hour™ Ayala Lampel, Julia Ortony

Ramaswamy, Claudia Clopath, Richard Naud, Andreas Tolias, Wei Wei

• Target-Specific Synaptic Function Ralf Schneggenburger, Peter Jonas, Jeff Magee, Xiang Yu

• Synaptic Dysfunction in Psychiatric Disorders Roger Nicoll, Guoping Feng

• The GRC Power Hour

™

Alison Barth

Systems Chemistry Fundamental Principles and Emergent Behavior within Networks of Molecules JUN 25-26, 2022 Chairs: Ignacio Colomer and Meagan Beatty

Michael Wessels, Melanie Hamon, Jose Lemos

• Host-Pathogen Interactions and the Fight for

Synaptic Transmission

Survival Anna Norrby-Teglund, Mattias Collin, David Aronoff, Annelies

Synaptic Function: From Molecules to Networks

Zinkernagel

JUN 18-19, 2022

• At the Surface of the Bacterial-Host Encounter Lakshmi Rajagopal, Angela Nobbs, Eric Schmidt, Nina van Sorge

• Interactions Within the Microbial Community Kimberly Kline, Katherine Lemon, Mohammad Seyedsayamdost, Joseph Zackular

• Phage and Mobile Genetic Elements Breck Duerkop, Kelli Palmer, Angela Brueggemann

CHAIRS: Hannah Monday and Simon Chamberland

Thiol-Based Redox Regulation and Signaling The Chemical Biology of Sulfur JUL 10-15, 2022 REY DON JAIME GRAND HOTEL, CASTELLDEFELS, SPAIN CHAIR: Kate Carroll VICE CHAIR: Joris Messens

• Keynote Session: Pioneers in Redox Regulation and

Signaling Ursula Jakob, Christine Winterbourn, Elias Arner

• Enabling Technologies for Redox Biology Gregory Payne, Vsevolod Belousov, Cristina Furdui, Derek Pratt, Yimon Aye, Che Pillay, Elizabeth New, Jing Yang

• Mechanisms of Thiol-Based Regulation Elizabeth Veal, Melissa Kemp, Fernando Antunes, Benoit Boivin, Pat Eyers, Brian Smith, W. Todd Lowther, Beatriz Alvarez

• Reactive Sulfur Species Michael Pluth, Peter Nagy, Kenneth Olson, Ming Xian, David Giedroc, Takaaki Akaike, Bindu Paul

• Mechanisms of Thiol-Based Signaling Leslie Poole, Albert Van Der Vliet, James Galligan, Carolyn Sevier, Tobias Dick, Cao Xu, Ana Denicola, Hadley Sikes

• Redox Medicine Ulla Knaus, Philip Eaton, Yvonne JanssenHeininger, Pietro Ghezzi, Carmen Wong, Bruce Freeman

• Redox Metabolism Keith Blackwell, Bruce Morgan, Carolina Greco, Canhua Huang, Oleh Khalimonchuk

• Selenoproteins and Reversible Methionine Oxidation Garry Buettner, Sina Ghaemmaghami, Robert Hondal, Rodney Levine, Vasanthi Viswanathan, Bruno Manta, Daniel Bak

• Grand Challenges and New Paradigms in Redox

• Emerging Diseases Laszlo Fesus, Mari Kaartinen, ZhaoQing Luo, Ian Maze, Christian Recktenwald

• Emerging Research Tools Reik Loeser, Diana Imhof, William Katt, Lakshmi Santhanam

• Cardiovascular Diseases Lakshmi Santhanam, Martin Griffin, In-Gyu Kim, Nicola Mutch, Michal Neeman

• Neurological Diseases Manuela Basso, Gail Johnson, Xianhua Piao, Anne-Marie Van Dam

• Cancer and Signaling Disorders Daniela Matei, Nicoletta Bianchi, Salvatore Condello, Soo-Youl Kim, Nicholas Peake

• Magnets and Heterostructures Roland Kawakami, Alberto Morpurgo, Daniel Ralph, Emanuel Tutuc

• Modeling Grand Challenges Di Xiao, Vladimir Falko, Allan Macdonald • Complex Phenomena Feng Wang, Kenneth Burch, David Cobden, Yuanbo Zhang

• Tunable Correlated States in Twisted 2D Materials Philip Kim, Cory Dean, Ali Yazdani, Andrea Young

• Emerging Phenomena David Tomanek, Hyeon-Jin Shin, Andres Castellanos-Gomez

• The GRC Power Hour™

• Celiac Disease and Inflammation Mauro Piacentini, Xian-Yang Qin, Detlef Schuppan, Yang Xia

• Fibrosis and Remodeling Patricia Sime, Timothy Johnson, James Luyendyk, Hideki Tatsukawa, Elisabetta Verderio

• Keynote Session: Activation and Inactivation of Tissue

Transglutaminase Anne-Marie Van Dam, Chaitan Khosla

Two Dimensional Electronics Beyond Graphene Fundamentals and Applications of Emerging 2D Crystals JUN 11-12, 2022 CHAIRS: Zhong Lin and Dmitry Ovchinnikov

• The GRC Power Hour™

Signaling Toren Finkel, Helmut Sies, Rafael Radi, Ruma Banerjee

Transglutaminases in Human Disease Processes

Unconventional Semiconductors NEW! and Their Applications

Thiol-Based Redox Regulation and Signaling

Pathology, Mechanism and Intervention of Transglutaminases

Physics, Chemistry and Applications of Metal-Halide Perovskites

Redox Signaling Factors: From the Molecular Mechanisms to the Physiological Consequences

JUN 11-12, 2022 CHAIR: Estéfano Pinilla Pérez

JUL 9-10, 2022 CHAIRS: Brandan Pedre Perez and Evanna Mills

Three Dimensional Electron Microscopy Technical Advances in 3DEM to Study Biological Structures Across Scales JUN 19-24, 2022 REY DON JAIME GRAND HOTEL, CASTELLDEFELS, SPAIN CHAIR: Daniela Nicastro VICE CHAIR: Radostin Danev

• Keynote Session: The Future of 3DEM in Structural

Biology: Beyond Cryo-EM Eva Nogales, Melanie Ohi • Advances in Specimen Preparation and

Workflows Hongwei Wang, Arjen Jakobi, Doryen Bubeck, Thamiya Vasanthakumar, Abraham Koster, Shengjie Feng

• 3DEM in Translational Research Pamela Williams, Claudio Ciferri, Shee-Mei Lok

• New Developments in Algorithms and Software Joachim Frank, Sjors Scheres, Jose Carazo, Ricardo Sánchez Loayza, Tristan Bepler

• Selected Poster Presentations Mario Borgnia • Frontiers in Cellular Tomography Julia Mahamid, Alex de Marco, Stefan Raunser, David Agard

• Structures In Situ: Pushing Resolution Limits John Briggs, Friedrich Foerster

Tribology Understanding Sliding Interfaces to Master Tribological Systems Across Length Scales

• Keynote Session: Opportunities and Challenges in

JUN 26-JUL 1, 2022 BATES COLLEGE, LEWISTON, ME CHAIR: Judith Harrison VICE CHAIR: Seong Kim

• Photovoltaics and Stability David Cahen, Antonio Abate, Kylie

• Understanding the Sliding Interface Filippo Mangolini, Nicolas Fillot, Prathima Nalam

• Adhesive Phenomena in Tribology Kathryn Wahl, Tevis Jacobs, Ramin Aghababaei, Jean Denape

• Probing the Sliding Interface Angela Pitenis, Antonella Rossi, James Schall

• Lamellar Solid Lubricants Thomas Scharf, John Curry, Clotilde Minfray, Andreas Rosenkranz

• Soft Tribology David Burris, Rosa M. Espinosa-Marzal, Alison Dunn • Tribology at the Extreme Marina Ruths, Pantcho Stoyanov, Joichi Sugimura, Satish Achanta

• Selected Poster Presentations Radostin Danev • The GRC Power Hour™

Three Dimensional Electron Microscopy Technical Advances in 3DEM and their Connection to Biological Breakthroughs JUN 18-19, 2022 CHAIRS: Cristina Puchades and Julia Peukes

Known and Emerging TransglutaminaseRelated Diseases and New Methods for Detection and Treatment JUN 12-17, 2022 MOUNT SNOW, WEST DOVER, VT CHAIR: Jeffrey Keillor VICE CHAIR: Kiyotaka Hitomi

• Keynote Session: Clinical Relevance of Tissue

Transglutaminase Elisabetta Verderio, Richard Eckert, Ludvig Sollid

Catchpole, Yabin Qi, Yang Yang

• Ion Migration Prashant Kamat, David Ginger, Mike McGehee, Elizabeth von Hauff

• Structure-Property Correlation Song Jin, Hemamala Karunadasa, Yanfa Yan, Peidong Yang

• Interfaces and Defects Barry P. Rand, Filippo De Angelis, Giulia Grancini, Annamaria Petrozza

• Carrier Dynamics Libai Huang, Laura Herz, Carlos Silva, Tze-Chien Sum, Xiaoyang Zhu

• Charge Transport Yuanyuan Zhou, Aditya Mohite, Valy Vardeny, Kai Zhu • Light Emission Samuel Stranks, Letian Dou, Maksym Kovalenko, Linn Leppert, Qihua Xiong

• Beyond PV and LED Joseph Berry, Biwu Ma • The GRC Power Hour™

Chromik, Alfons Fischer, Christian Greiner

• Electric Vehicle and Green Tribology Brian Borovsky, Arup Gangopadhyay, Peter Lee, Farrukh Qureshi

• Keynote Session: Tribology for Health Seong Kim, Robert Carpick • The GRC Power Hour™ Alison Dunn, Jacqueline Krim

Unifying Ecology Across Scales Integrating Theory and Empiricism in Ecology and Evolution through Energetics, Elements, and Information

Understanding Sliding Interfaces to Master Tribological Systems Across Length Scales

JUL 31-AUG 5, 2022 SOUTHERN NEW HAMPSHIRE UNIVERSITY, MANCHESTER, NH CHAIR: Angelica Gonzalez VICE CHAIR: John DeLong

JUN 25-26, 2022

• Keynote Session: Integration and Synthesis in Ecology and

Tribology

CHAIRS: Nathaniel Hawthorne and Yijue Diao

Two Dimensional Electronics Beyond Graphene Emerging Complex Phenomena and Applications

Transglutaminases in Human Disease Processes

Metal-Halide Perovskites David Mitzi, Tsutomu Miyasaka

• Tribologically-Induced Surface Changes and Wear Richard

• Innovations of Instruments and Hardware Robert Glaeser, Holger Mueller, Keiichi Namba, Peiyi Wang, Saori Maki-Yonekura

JUN 12-17, 2022 FOUR POINTS SHERATON, HOLIDAY INN EXPRESS, VENTURA, CA CHAIRS: Matthew Beard and Jinsong Huang VICE CHAIRS: Hanwei Gao and Iván Mora-Seró

JUN 12-17, 2022 SOUTHERN NEW HAMPSHIRE UNIVERSITY, MANCHESTER, NH CHAIRS: Xiaodong Xu and Deji Akinwande VICE CHAIRS: Jie Shan and Frank Koppens

• Synthesis and Characterization Anna Isaeva, James Hone, Jiwoong Park

• Device Applications Fengnian Xia, Peide Ye, Iluliana Radu • Collective Excitation Tony Heinz, Kin Fai Mak, Pablo Jarillo-Herrero, Marco Polini

• Quantum and Nonlinear Optical Effects Hongkun Park, Hui Deng, Atac Imamoglu

Evolution Through Fundamental Principles Helmut Hillebrand, Pablo Marquet, Elizabeth Borer

• Causal Links between Temperature, Metabolism and

Stoichiometry Anita Narwani, Elena Litchman, Sean Michaletz, Joey Bernhardt, Alexis Synodinos, Daniel Wieczynski

• Variation in Biological Scaling and the Four Dimensions of

Life Joanna Bernhardt, James Brown, Anastassia Makarieva, Ian Hatton • Evolutionary Underpinnings of Ecological Physiology Theodore Garland, Lauren Buckley, Christopher Kempes, Jennifer Sunday, Seth Rudman, Juan Vicente Gallego Rubalcaba

• Integrating Theories to Explain Ecological Patterns and

Processes Across Spatial Scales Dominique Gravel, Jordan Okie, Adam Clark, Cristian Roman Palacios, Melissa Guzman

• Wrapped Hierarchies and Disease Ecology: The Interplay

of Ecological and Evolutionary Theories Andy Dobson, Mercedes Pascual, Cynthia Downs, Dedmer Van de Waal, Ann Tate • Time Continuum: Synergies Between Paleoecological and

Neoecological Perspectives Michelle Lawing, Jessica Blois, Kate Lyons, Graciela Gil-Romera

• Multitrophic Species Interactions and the Functioning of

Ecosystems Serguei Saavedra, Priyanga Amarasekare, Oscar Godoy, Pablo Antiqueira

• Keynote Session: Challenges and Opportunities for an

Integrative Ecology Jeremy Fox, Brian McGill, Felisa Smith • The GRC Power Hour™ Jennifer Sunday, John DeLong

Unifying Ecology Across Scales Integrating Ecological Currencies Across Scales From Cells to Ecosystems JUL 30-31, 2022 CHAIRS: Joey Bernhardt and Daniel Wieczynski

Vibrational Spectroscopy Unravelling Chemical Heterogeneity JUL 31-AUG 5, 2022 BRYANT UNIVERSITY, SMITHFIELD, RI CHAIRS: Lauren Webb and Aaron Massari VICE CHAIRS: Judy Kim and Poul Petersen

• Complex Charged Liquids Amber Krummel, Steven Corcelli, Franz Geiger, Heather Allen

• Biological Complexity at Surfaces Elsa Yan, Jennifer Lee, Wei Zhuang, Lu Wang, Vicki Grassian

• Biological Complexity in Solution Scott Brewer, Steven Boxer, Casey Londergan, Carlos Baiz

• Non-Neuronal Cells and Tissues Ruth Ashery-Padan, Ruby Shalom-Feuerstein, Monica Vetter, Sumiko Watanabe

• Central Visual Development and Sensory Integration David Feldheim, Xin Duan, Samer Hattar, Takao Hensch, Chi-hon Lee, Hongkui Zeng

• Development and Dysfunction of the Primate Retina Robert Johnston, Rod Bremner, Jay Gopalakrishnan, Anna La Torre

• Cellular Regeneration and Stem Cells Michel Cayouette, Katia Del Rio-Tsonis, Mike Karl, Jeff Mumm, Kapil Bharti, Carol Schuurmans

• Emerging Systems for Studying Visual

Development Tiffany Cook, Belinda Chang, Joseph Corbo, Kristen Koenig, Wei Li

• The GRC Power Hour™ Monica Vetter

• Environmental Applications of Vibrational

Venom Evolution, Function and Biomedical Applications Bridging Gaps in Venom Research: From Ecology and Evolution to Socio-Economic Impacts AUG 7-12, 2022 MOUNT SNOW, WEST DOVER, VT CHAIRS: Ashlee Rowe and Glenn King VICE CHAIRS: Stephen Mackessy and Irina Vetter

• Keynote Session: Functional Ecology and Biodiversity of

Venom Yehu Moran, Maria Modica, Kartik Sunagar • Ecological and Evolutionary Processes Shaping Venoms:

Connecting Basic Research with Downstream Applications Ricardo Rodriguez de la Vega, Darin Rokyta, Maria Peichoto

• Emerging Models in Venom Research Andrew Walker, Mande

Spectroscopy Amanda Mifflin, Jana Roithova, Mark Johnson, Cristina Puzzarini, Sharon Hammes-Schiffer

• Unorthodox Vibrational Spectroscopy Melanie Reber, Jordan Hachtel, Quentin Ramasse, Fancesca Palombo

• Heterogenous Catalytic Systems Jahan Dawlaty, Sandra Luber, Renee Frontiera, Wei-Tao Liu, Alexander Cowan

Approaches Beatrix Ueberheide, Greg Neely, Eivind Undheim • Toxin Structure and Function Gregor Anderluh, R. Manjunatha Kini, Markus Muttenthaler

• Characterizing Toxin-Target Interactions Micaiah Ward, Jian

George Schatz, Wei Min, Katarzyna Marzec

• Vibrational Spectroscopy at Charged Interfaces John Asbury, Sylvie Roke, Andrei Tokmakoff, Marie-Pierre Gaigeot, Julianne Gibbs

• New Approaches to Obtain Vibrational Information Thomas Allison, Aaron Rury, Adam Dunkelberger, Hui Li

• The GRC Power Hour™ Elsa Yan, Judy Kim

Nicholas Casewell, Andreas Laustsen, Julian White, Leslie Boyer

• Biomedical and Pesticidal Applications of

Venom Baldomero Olivera, Maria Ikonomopoulou, Helena Safavi, Volker Herzig

• Keynote Session: Socio-Economic and Human Health

Impacts of Venom Irina Vetter, José María Gutiérrez, Abdulrazaq Habib, Robert Kennedy

• The GRC Power Hour™ Nancy Ryan Gray

Bridging Gaps in Venom Research: From Ecology and Evolution to Socio-Economic Impacts AUG 6-7, 2022 CHAIRS: Aida Verdes and Micaiah Ward

Chairs: Cameron Prigge and Chi Sun

Water and Aqueous Solutions Water on Multiple Length Scales From the Molecular Level to the Global Hydrosphere JUL 24-29, 2022 HOLDERNESS SCHOOL, HOLDERNESS, NH CHAIR: Mary Jane Shultz VICE CHAIR: Susan Rempe Johnson, Anne McCoy

Interrogating Chemical Structures, Functions and Dynamics Using Molecular Vibrations

• Nonlinear Surface Probes THz to UV Dennis Hore, Mischa

JUL 30-31, 2022

• Modeling Nonlinear Spectra Heather Allen, Francesco Paesani,

Chairs: Kajari Bera and Mark Babin

Bonn, Marie-Pierre Gaigeot, Tahei Tahara Richard Saykally

• Clathrate Hydrates Packaging Water Qiang Cui, Larry Anovitz,

Visual System Development Building and Rebuilding the Visual System: From Genes to Cells to Circuits AUG 14-19, 2022 SOUTHBRIDGE HOTEL & CONFERENCE CENTER, SOUTHBRIDGE, MA CHAIR: Seth Blackshaw VICE CHAIR: Valerie Wallace

• Keynote Session: Frontiers in Visual Systems Development

and Disease Nadean Brown, Thomas Reh, Masayo Takahashi

Venom Evolution, Function and Biomedical Applications

AUG 13-14, 2022

• Smallest Scale: Few Water Clusters Michael Duncan, Mark

Vibrational Spectroscopy

Payandeh, Ray Norton, Evelyne Deplazes

• Antivenom: Advances in Development and Production

Establishing a Visual System: From Retinal Cell Fate to Higher Order Connectivity and Processing

• Vibrational Spectroscopy on the Nanoscale Wei Xiong,

Holford

• Advances in Technological and Methodological

Visual System Development

• From Retinal Patterning to Cell Fate Specification Kristen Kwan, Susana da Silva, Vilaiwan Fernandes, Jin Woo Kim, Justin Kumar, Simon Sprecher

• Genome-Wide Approaches for Studying Visual Development Michael Dyer, Rui Chen, Brian Clark, Xin Li, Xiaoqun Wang

• Building, Remodeling and Repairing Retinal

Circuitry Jeremy Kay, Robin Hiesinger, Melanie Samuel, Enrica Strettoi, Julie Lefebvre, Iris Salecker

Anastasia Ilgen, Tod Pascal

• Water Mediated Aggregation Douglas Tobias, Heloisa Bordallo, Kenneth Dill

• Neutron Probes in the Bio Realm Lorena Tribe, Dor Ben-Amotz, Steve Seibner, Nonne Prisle

• Water in the Atmosphere: Ice Nucleation and Growth Emily Asenath-Smith, Ruth Signorell, Petr Slavicek

• Selected Poster Presenters Revati Kumar, Bertrand Chazallon, Teresa Head-Gordon

• Water Enveloping the Earth from the Subsurface to the

Stratosphere Veronica Vaida, Antonio Mannino • The GRC Power Hour™

Water and Aqueous Solutions Water on Multiple Length Scales From the Molecular Level to the Global Hydrosphere JUL 23-24, 2022 Chairs: Clara-Magdalena Saak and Elise Duboue-Dijon

online @sciencecareers.org

FACULTY OPPORTUNITY:

Institute for Genomic Medicine at Nationwide Children’s Hospital The Institute for Genomic Medicine (IGM) combines a robust clinical laboratory with cutting-edge research in molecular and computational biology to optimize patient care. The IGM’s primary mission is to move genomics-based research results into the mainstream of diagnosis and treatment, making the results accessible and meaningful for patients and families.

About the Faculty Position: • Seeking Associate or Full Professor • Candidate should have a research laboratory with a focus on immunology/immunogenetics, cardiac or GI developmental biology or polygenic risk score calculations for predictive complex disease risk Qualifications Required: • MD, MD/PhD, or PhD • Strong track record of publishing in high IF journals • Current R01 or equivalent federal grant funding is preferred

Send correspondence, including CV, brief statement of research interests, and contact information for three references to: Richard Wilson, PhD, and Elaine Mardis, PhD, c/o [email protected]

W552400

IT’S NOT JUST A JOB. IT’S A CALLING. Find your next job at ScienceCareers.org

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online @sciencecareers.org

Open Rank Tenure Track Faculty Positions The College of Science and Mathematics (CSM) at Kennesaw State University, one of the fastest growing universities in Georgia, seeks several new tenure track faculty to join our diverse community of researchers. Positions are available at the Assistant, Associate, or Professor rank for individuals who are committed to contributing to an inclusive and equitable work environment. Specifically, we are interested in candidates with research programs in: Microorganism or parasite chemical biology, infection, or drug discovery. Seeking to understand microorganisms or parasites using functional, phenotypic, chemical, genetic, and structure-based methods. (Job ID# 238131) Examples of programs: Chris Cornelison (https://bioinnovation.kennesaw.edu/research/) Thomas C. Leeper (https://facultyweb.kennesaw.edu/tleeper/index.php) Kojo Mensa-Wilmot (https://facultyweb.kennesaw.edu/kmensawi/research.php) Molecular basis of disease in model systems. Research may integrate genetic, chemical, biophysical, and structural approaches to molecular underpinnings of disease in cellular, tissue, and animal models. (Job ID# 238108) Examples of programs: Martin Hudson (https://facultyweb.kennesaw.edu/mhudso28/research.php) Scott Nowak (https://facultyweb.kennesaw.edu/snowak/nowak-lab/research.php) Learn more about CSM research at https://csm.kennesaw.edu/research/research-interest-groups/index.php Do you want to... • • • •

Contribute to development of exciting new interdisciplinary programs? Work in outstanding research facilities? Receive competitive compensation and benefits, relocation assistance and startup research packages? Join a college that values inclusive excellence and diversity of faculty?

Then, we want you! How to apply:

1.Visit https://hr.kennesaw.edu/careers.php 2.Click Faculty & Staff Openings 3.Click View all Jobs 4.Search Job ID 238131 or 238108

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WORKING LIFE By Julie R. Posselt

It’s not (all) about you

I’ve worked in and studied graduate admissions for almost 20 years, and perhaps the most fundamental misconception is that the best applicants win. The truth is that what counts as an “ideal” applicant is a moving target. The process can be unfair—even unjust. Practical considerations also play a role, starting with the reality that programs have limited funding and advising capacity. Either way, the reasons for rejection are often as much about the professors and programs as they are about the applicants. Here are some scenarios I’ve witnessed. FACULTY HOLD BIASES. Outcomes

It’s common to want “balance”— groups of admitted students that are diverse on many dimensions, including their social identities and research interests. Applicants don’t know and can’t control who else has applied, but they unwittingly affect one another’s odds. COMMITTEES CAN BE RISK AVERSE. I

“In admissions, like any game, you will win some and lose some.”

of graduate admissions can be especially unpredictable for students from marginalized groups. For example, gender bias no doubt contributed to the rejection of the woman whose interview I observed more than 10 years ago; her friendly persona didn’t comport with the panel’s idea of “gravitas.” Bias is a major, multifaceted problem— which is why faculty should reflect on and discuss their admissions priorities, learn what current research says about selection and bias, and develop shared standards. THE FIT WAS OFF. I have been on committees put in the un-

comfortable position of rejecting applicants with stellar grades, mountains of research experience, and powerful personal statements—simply because their research interests didn’t align with the specific, immediate needs of a faculty member. Applicants can help their chances by clearly articulating how their interests and experiences match those of prospective advisers. IT WAS ABOUT THE COHORT. Great applicants are often re-

jected because faculty are thinking not only about individual students, but also the cohort they want to enroll.

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25 FEBRUARY 2022 • VOL 375 ISSUE 6583

once observed an admissions committee decline an applicant from a top-ranked university who had seven first-authored publications under his belt. The faculty were so convinced he’d be admitted to a higher ranked program that they didn’t want to take a chance by giving him an offer. Instead they accepted applicants they thought were more likely to attend. It underscores why applicants should only apply to programs where they can make a compelling case for their interest. THEY DON’T WANT TO FIGHT. If two professors are keen to

advise the same applicant and there are no structures for coadvising, then professors may protect their relationship with each other by simply rejecting the applicant rather than fighting about it. Collegiality is a virtue in academia, but it doesn’t always benefit students. Admissions decisions involve more than a judgment of an applicant’s worth and potential. If you’re among the thousands of prospective graduate students who receive rejection letters each year, perhaps these insights into the process can help you reframe rejection. It’s natural to be frustrated, but keep in mind that in admissions, like any game, you will win some and lose some. Keep playing! j Julie R. Posselt is an associate dean of the graduate school at the University of Southern California. Do you have an interesting career story to share? Send it to [email protected].

science.org SCIENCE

ILLUSTRATION: ROBERT NEUBECKER

S

miling through the interrogation of an online Ph.D. admission interview, a woman of color confidently answered questions posed by three men huddled around a laptop. I sat behind them, observing as a researcher studying the admissions process. In my view, she handled their questions brilliantly—stressing her qualifications and articulating creative research ideas. But the next week, when her application came up in committee deliberations, the decision to reject her was swift and unanimous. I was shocked. One faculty member commented, “Ugh, I wondered if she’d ever stop smiling.” Another replied, “No kidding. Too much sunshine, not enough gravitas.”

CA L L F O R PA P E R S

spj.sciencemag.org/bmef

BMEF is a Science Partner Journal distributed by the American Association for the Advancement of Science (AAAS) in collaboration with the Suzhou Institute of Biomedical Engineering and Technology, Chinese Academy of Sciences (SIBET CAS). BMEF serves the multidisciplinary community of biomedical engineering by publishing breakthrough original Research Articles, Rapid Reports, Reviews, Perspectives, and Editorials. The journal also publishes research in the fields of pathogenic mechanisms as well as disease prevention, diagnosis, treatment, and assessment. The Science Partner Journals (SPJ) program was established by the American Association for the Advancement of Science (AAAS), the nonprofit publisher of the Science family of journals. The SPJ program features high-quality, online-only, open access publications produced in collaboration with international research institutions, foundations, funders and societies. Through these collaborations, AAAS expands its efforts to communicate science broadly and for the benefit of all people by providing top-tier international research organizations with the technology, visibility and publishing expertise that AAAS is uniquely positioned to offer as the world’s largest general science membership society.

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